2021 | 1. | Mehta, M., Pattel, M., Fournier-Viger, P., Lin, J. C.-W. (editors). Tracking and Preventing Diseases using Artificial Intelligence. Springer, 2021, in preparation - Call for chapters - deadline passed |
2. | Kiran, R. U., Fournier-Viger, P., Mondal, A., Luna, J.M., Lin, J. C.-W. (editors) Periodic Pattern Mining: Theory, Algorithms and Applications, Springer, 2021, in preparation - Call for chapter proposals - deadline passed | |
2020 | 3. | Chiroma, H., Abdulhamid, S. M., Fournier-Viger, P., Garcia, N. M. (editors). Machine learning and Data Mining for Emerging Trends in Cyber Dynamics. Springer, 2021, |
2019 | 4. | Fournier-Viger, P., Lin. J. C.-W., Vo, B., Nkambou, R., Tseng, V. S. (editors). High-Utility Pattern Mining: Theory, Algorithms and Applications, Springer, 2019. |
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2021 | 1. | Nouioua, M., Fournier-Viger, P., He, G., Nouioua, F., Min, Z. (2020). A Survey of Machine Learning for Network Fault Management. In the book “Machine Learning and Data Mining for Emerging Trends in Cyber Dynamics”, Springer, to appear. |
Fournier-Viger, P. et al. (2021). Finding Periodic Patterns in Multiple Discrete Sequences. In the book “Periodic Pattern Mining: Theory, Algorithms and Application”, Springer, to appear. | ||
2019 | 2. | Fournier-Viger., P., Lin, J. C.-W., Truong, T., Nkambou, R. (2019). A survey of high utility itemset mining. In: Fournier-Viger et al. (eds). High-Utility Pattern Mining: Theory, Algorithms and Applications, Springer (to appear), p. 1-46. DOI: 10.1007/978-3-030-04921-8_1 |
3. | Qu, J.-F., Liu, M., Fournier-Viger (2019). Efficient algorithms for high utility itemset mining without candidate generation. In: Fournier-Viger et al. (eds). High-Utility Pattern Mining: Theory, Algorithms and Applications, Springer, p. 131-160. DOI: 10.1007/978-3-030-04921-8_5 |
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4. | Truong, T., Fournier-Viger., P. (2019). A survey of high utility sequential pattern mining. In: Fournier-Viger et al. (eds). High-Utility Pattern Mining: Theory, Algorithms and Applications, Springer, p. 97-130. DOI: 10.1007/978-3-030-04921-8_4 |
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5. | Dinh, D.-T., Huynh, V.-N., Le, B., Fournier-Viger, P., Huynh, U., Nguyen, Q.-M. (2019). A Survey of Privacy Preserving Utility Mining.In: Fournier-Viger et al. (eds). High-Utility Pattern Mining: Theory, Algorithms and Applications, Springer, p.207-232 DOI: 10.1007/978-3-030-04921-8_8 |
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6. | Djenouri, Y., Fournier-Viger, P., Belhadi, A., Lin, J. C.-W. (2019). Methaheuristics for High Utility and Frequent Itemset Mining . In: Fournier-Viger et al. (eds). High-Utility Pattern Mining: Theory, Algorithms and Applications, Springer, p. 261-278. DOI: 10.1007/978-3-030-04921-8_10 |
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7. | Wu. C.-W., Fournier-Viger, P., Gu, J. Y., Tseng, V.S. (2019). Mining Compact High Utility Itemsets without Candidate Generation. In: Fournier-Viger et al. (eds). High-Utility Pattern Mining: Theory, Algorithms and Applications, Springer. DOI: 10.1007/978-3-030-04921-8_11 |
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2015 | 8. | Snow, E., Moghrabi, C., Fournier-Viger, P. (2015). Automatic Grading of Open-ended Questions Using Semantic Web Ontologies and Functional Concepts. In. Taylor, K., Gerber, A., Meyer, T., Orgun, M. (Eds.) Ontologies: Theory and Applications in Information Systems and the Semantic Web, 12 pages. |
2013 | 9. | Faghihi, U., Fournier-Viger, P., Nkambou, R. (2013). CELTS: A Cognitive Tutoring Agent with Human-Like Learning Capabilities and Emotions. In Ayala, A. P. (Ed.) Intelligent and Adaptive Educational-Learning Systems: Achievements and Trends, Springer, pp. 339-365.1 |
<2010 | 10. | Fournier-Viger, P., Nkambou, R., Mephu Nguifo, E. (2010). Building Intelligent Tutoring Systems for Ill-Defined Domains. In Nkambou, R., Mizoguchi, R., Bourdeau, J. (Eds.). Advances in Intelligent Tutoring Systems, Springer, p.81-101. |
11. | Fournier-Viger, P., Nkambou, R., Mephu Nguifo, E. (2010). Learning Procedural Knowledge from User Solutions To Ill-Defined Tasks in a Simulated Robotic Manipulator. In Romero et al. (Eds.). Handbook of Educational Data Mining, CRC Press, p. 451-465. | |
12. | Fournier-Viger, P., Nkambou, R., Faghihi, U., Mephu Nguifo, E. (2009). Mining Temporal Patterns to Improve Agents Behavior: Two Case Studies. In Cao, L. (Ed.) Data Mining and Multiagent Integration, Springer, p.77-92. |
Indexes / SCR rank / ISSN | |||
2021. | 1. | ... Lin, J.C.W., ... Fournier-Viger, P. ... (2021). Hiding Sensitive Information in eHealth Datasets. Future Generation Computer Systems, Elsevier, to appear. |
ISI, EI, SCI, |
2. | Fournier-Viger, P., Wang Y., Yang, P., Lin, J. C.-W., Yun, U. (2021). TSPIN: Mining Top-k Stable Periodic Patterns. Applied Intelligence, to appear. | ISI, EI, SCI, Q2 IF: 3.264 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C, corr. auth. |
|
3. | Nouioua, M., Fournier-Viger, P., W. C.-W., Lin, J. C.-W., Gan, W. (2021). FHUQI-Miner: Fast High Utility Quantitative Itemset Mining. Applied Intelligence, to appear. | ISI, EI, SCI, Q2 IF: 3.264 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C, corr. auth. |
|
4. | Nawaz, S., Fournier-Viger, P., Shojaee, A., Fujita, H. (2021). Using Artificial Intelligence Techniques for COVID-19 Genome Analysis. Applied Intelligence, to appear. [code and data + SPMF] | ISI, EI, SCI, Q2 IF: 3.264 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C, corr. auth. |
|
5. | Nawaz, M.S., Nawaz, M.Z., Hasan, O, Fournier-Viger, P., Sun, M. (2021). An Evolutionary/Heuristic-Based Proof Searching Framework for Interactive Theorem Prover. Applied Soft Computing, Elsevier. to appear | ISI, EI, SCI, |
|
6. | Gan, W., Lin, J. C. W., Zhang, J., Yin, H., Fournier-Viger, P., Chao, H.-C., Yu, P. S. (2021) Utility Mining Across Multi-Dimensional Sequences. ACM Transactions on Knowledge Discovery from Data (TKDD), to appear | ISI, EI, SCI, SCR: Q1 IF: 2.8 ISSN: 1556-4681 CA: Q4 JCR: Q2 CCF-B |
|
7. | Kim, H., Yun, U., Baek, Y., Kim, H., Nam, H., Lin, J. C.-W., Fournier-Viger, P. (2021). Damped Sliding Window based Utility Pattern Mining over Stream Data. Knowledge-based Systems, Elsevier, 213(15):106653 DOI: 10.1016/j.knosys.2020.106653 |
ISI, EI, SCI, Q1
IF: 5.3 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C |
|
2020. | 8. | Gan, W., Lin, J. C.-W., Fournier-Viger, P., Zhang. J., Chao, H.-C., Yu, P. S. (2020). Fast Utility Mining on Sequence Data. IEEE Transactions on Cybernetics. IEEE. 51(2), 487-500 |
ISI, EI, SCI,
Q1 IF: 11.469 ISSN: 2168-2267 CA: Q1 JCR: Q1 CCF-B |
9. | Qu, J., Fournier-Viger, P., Liu, M., Hang, B., Wang, F. (2020) Mining High Utility Itemsets Using Extended Chain Structure and Utility Machine. Knowledge-Based Systems (KBS), Elsevier, 208:106457 DOI: 10.1016/j.knosys.2020.106457 |
ISI, EI, SCI, Q1
IF: 5.3 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C |
|
10. | Gan, W., Lin, J., Fournier-Viger, P., Chao, H.C., Yu, P.S. (2020). Beyond Frequency: Utility Mining with Varied Item-Specific Minimum Utility. ACM Transactions on Internet Technology, ACM, to appear. |
ISI, EI, SCI, |
|
11. | Shabtay, L., Fournier-Viger, P., Yaari, R., Dattner, I. (2020). A Guided FP-growth algorithm for mining multitude-targeted item-sets and class association rules in imbalanced data. Information Sciences, Elsevier, to appear. DOI: 10.1016/j.ins.2020.10.020 |
ISI, EI, SCI, Q1 IF: 5.3 ISSN: 0020-0255 CA: Q2 JCR: Q1 CCF-B |
|
12. | Fournier-Viger, P., Yang, P., Kiran, R. U., Ventura, S., Luna, J. M.. (2020). Mining Local Periodic Patterns in a Discrete Sequence. Information Sciences, Elsevier, to appear. [source
code] [ppt] |
ISI, EI, SCI, Q1 IF: 5.3 ISSN: 0020-0255 CA: Q2 JCR: Q1 CCF-B, corr. auth. |
|
13. | Fournier-Viger, P., He, G., Cheng, C., Li, J., Zhou, M., Lin, J.C-W., Yun, U. (2020). A Survey of Pattern Mining in Dynamic Graphs. WIREs Data Mining and Knowledge Discovery, Wiley, DOI: 10.1002/WIDM.1372 |
ISI, EI, SCI, Q1 IF: ISSN: 1942-4787, corr. auth. |
|
14. | Liu, X., Niu, X., Fournier-Viger, P. (2020) Fast Top-K Association Rule Mining Using Rule Generation Property Pruning. Applied Intelligence, Springer, to appear |
ISI, EI, SCI, Q2 IF: 3.264 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C, corr. auth. |
|
15. | Nawaz, S., Nawaz, Z, Hasan, O., Fournier-Viger, P., Sun, M. (2020) Proof Searching and Prediction in HOL4 with Evolutionary/Heuristic and Deep Learning Techniques. Applied Intelligence, Springer, to appear |
ISI, EI, SCI, Q2 IF: 3.264 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C, corr. auth. |
|
16. | Noor, S., Guo, Y., Shah, S. H. H., Fournier-Viger, P., Nawaz, M. S. (2020). Analysis of Public Reaction to the Novel Coronavirus (COVID-19) Outbreak on Twitter. Kybernetes, Emerald Publishing DOI: 10.1108/K-05-2020-0258 |
SCI ... IF: 2.394 ISSN: 0368-492X CA: ..... |
|
17. | Lin, J., Li, Y., Fournier-Viger, P., Djenouri, Y., Zhang, J. (2020). Efficient Chain Structure for High-Utility Sequential Pattern Mining. IEEE Access, 8: 40714-40722 DOI: 10.1109/ACCESS.2020.2976662 |
ISI, EI, SCI, SCR: Q2 IF: 4.098 ISSN: 2169-3536 CA: Q2 JCR: Q1 |
|
18. | Nawaz, S., Fournier-Viger, P., Lin, J. C.-W., Zhang, J. (2020). Proof Learning in PVS with Utility Pattern Mining. IEEE Access, 8: 119806-119818 DOI: 10.1109/ACCESS.2020.3004199 |
ISI, EI, SCI, SCR: Q2 IF: 4.098 ISSN: 2169-3536 CA: Q2 JCR: Q1, corr. auth. |
|
19. | Vo, B., Nguyen, T.T., Nguyen, T. D. D., Fournier-Viger, P., Yun, U. (2020). A multi-core approach to efficiently mine high-utility itemsets in dynamic profit databases. IEEE Access, 9(1):85890-85899. DOI: 10.1109/ACCESS.2020.2992729 |
ISI, EI, SCI, SCR: Q2 IF: 4.098 ISSN: 2169-3536 CA: Q2 JCR: Q1 |
|
20. | Luna, J.M., Fournier-Viger, P., Ventura, S. (2020). Extracting user-centric knowledge on two different spaces: concepts and records. IEEE Access, 8(1):134782-134799. DOI: 10.1109/ACCESS.2020.3010852 |
ISI, EI, SCI, SCR: Q2 IF: 4.098 ISSN: 2169-3536 CA: Q2 JCR: Q1 |
|
21. | Li, X., Li, J., Fournier-Viger, P., Nawaz, M. S., Yao, J., Lin, J. C.-W. Mining Productive Itemsets in Dynamic Databases. IEEE Access, 8:140122-140144. DOI: 10.1109/ACCESS.2020.3012817 |
ISI, EI, SCI, SCR: Q2 IF: 4.098 ISSN: 2169-3536 CA: Q2 JCR: Q1, corr. auth. |
|
22. | Frnda, J., Durica, M., Savrasovs, M., Fournier-Viger, P., Lin, J. C.-W. (2020). QoS to QoE Mapping Function for Iptv Quality Assessement Based on Kohonen Map: A Pilot Study. Transport and Telecommunication, Sciendo, 21(3), 181-190. DOI: 10.2478/ttj-2020-0014 |
ESCI |
|
23. | Frnda, J., ... Fournier-Viger, P. ... (2020). A New Perceptual Evaluation Method of Video Quality Based on Neural Network. Intelligent Data Analysis, IOS Press (to appear) DOI: |
ISI, EI, SCI, IF: 0.86 ISSN 1088-467X CA: Q4 JCR: Q4 CCF-C |
|
24. | Yun, U., Kim, J., Yoon, E., Lin, J.C.W., Fournier-Viger, P. (2020). One scan based High Average-Utility Pattern Mining in static and dynamic databases. Future Generation Computer Systems, Elsevier, to appear. DOI: 10.1016/j.future.2020.04.027 |
ISI, EI, SCI, |
|
25. | Truong, T.T., Tran, A., Duong, H., Le, B., Fournier-Viger, P. (2020). EHUSM: Mining High Utility Sequences with a Pessimistic Utility Model. Data Science and Pattern Recognition (DSPR), to appear. | ISSN: 2520-4165 Note: special issue of UDM 2018 workshop papers |
|
26. | Fournier-Viger, P., Li, J., Lin, J. C.-W., Truong, T. (2020). Discovering low-cost high utility patterns. Data Science and Pattern Recognition (DSPR), Vol. 4(2), pp. 50–64, 2020. | ISSN: 2520-4165, corr. auth. Note: special issue of UDM 2018 workshop papers |
|
2019 | 27. | Baek, Y., Yun, U., Yoon, E., Fournier-Viger P. d(2019). Uncertainty based Pattern Mining for Maximizing Profit of Manufacturing Plants with List Structure. IEEE Transactions on Industrial Electronics, IEEE. 67(11):9914-9926. DOI: 10.1109/TIE.2019.2956387 |
ISI, EI, SCI SCR: Q1 IF: 7.05 ISSN: 0278-0046 CA: Q1 JCR: Q1 |
28. | Gan, W., Lin, J. C.-W., Fournier-Viger, P., Chao, H.-C., Tseng, V. S., Yu, P. (2019). A Survey of Utility-Oriented Pattern Mining. IEEE
Transactions on Knowledge and Data Engineering (TKDE), to appear... DOI: 10.1109/TKDE.2019.2942594 |
ISI, EI, SCI, SCR: Q1 IF: 4.561 ISSN: 1041-4347 CA: Q2 JCR: Q1 CCF-A |
|
29. | Truong, T., Duong, H., Le, B., Fournier-Viger, P. (2019). Efficient Vertical Mining of High Average-Utility Itemsets based on Novel Upper-Bounds. IEEE Transactions on Knowledge and Data Engineering (TKDE), 31(2): 301 - 314. | ISI, EI, SCI, Q1 IF: 4.561 ISSN: 1041-4347 CA: Q2 JCR: Q1 CCF-A |
|
30. | Fournier-Viger, P., Li, J., Lin, J. C., Chi, T. T., Kiran, R. U. (2019). Mining Cost-Effective Patterns in Event Logs. Knowledge-Based Systems (KBS), Elsevier, 191: 105241 [ppt] [source code] DOI: 10.1016/j.knosys.2019.105241 |
ISI, EI, SCI, Q1
IF: 5.3 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C, corr. auth. |
|
31. | Fournier-Viger, P., Cheng, C., Cheng, Z., Lin, J. C.-W., Selmaoui-Folcher, N. (2019). Mining Significant Trend Sequences in Dynamic Attributed Graphs. Knowledge-Based Systems (KBS), Elsevier, to appear. [source
code] [ppt] DOI: 10.1016/j.knosys.2019.06.005 |
ISI, EI, SCI, Q1
IF: 5.3 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C, corr. auth. |
|
32. | Truong, T., Duong, H., Le, B., Fournier-Viger, P., Yun, U. (2019). Efficient High Average-Utility Itemset Mining Using Novel Vertical Weak Upper-Bounds. Knowledge-Based Systems (KBS), Elsevier, 31(2): 301-314 DOI: 10.1016/j.knosys.2019.07.018 |
ISI, EI, SCI, Q1
IF: 5.3 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C, corr. auth. |
|
33. | Nguyen, L, Nguyen, P., Nguyen, T., Vo, B., Fournier-Viger, P., Tseng, V. S. (2019). Mining High Utility Itemsets in Dynamic Profit Databases. Knowledge-Based Systems (KBS), Elsevier,175: 130-144. DOI: 10.1016/j.knosys.2019.03.022 |
ISI, EI, SCI, Q1
IF: 5.3 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C |
|
34. | Fournier-Viger, P., Zhang, Y., Lin, J. C.W., Fujita, H., Koh, Y.S. (2019). Mining Local and Peak High Utility Itemsets. Information Sciences, Elsevier, 481: 344-367. [source code][ppt] DOI: 10.1016/j.ins.2018.12.070 |
ISI, EI, SCI, Q1 IF: 5.3 ISSN: 0020-0255 CA: Q2 JCR: Q1 CCF-B, corr. auth. |
|
35. | Fournier-Viger, P., Li, Z., Lin, J. C. W., Kiran, R. U., Fujita, H. (2019). Efficient Algorithms to Identify Periodic Patterns in Multiple Sequences. Information Sciences, Elsevier, 489: 205-226 [source
code][ppt] DOI: 10.1016/j.ins.2019.03.050 |
ISI, EI, SCI, Q1 IF: 5.3 ISSN: 0020-0255 CA: Q2 JCR: Q1 CCF-B, corr. auth. |
|
36. | Truong, T., Duong, H., Le, B., Fournier-Viger, P. (2019). EHAUSM: An Efficient Algorithm for High Average Utility Sequence Mining. Information Sciences, Elsevier, 515: 302-323. |
ISI, EI, SCI, Q1 IF: 5.3 ISSN: 0020-0255 CA: Q2 JCR: Q1 CCF-B |
|
37. | Lin, J. C.-W., Shao, Y., Fournier-Viger, P., Fujita, H. (2019). BILU-NEMH: A BILU Neural-Encoded Mention Hypergraph for Mention-Extraction. Information Sciences, Elsevier, 496: 53-64. DOI: 10.1016/j.ins.2019.04.059 |
ISI, EI, SCI, Q1 IF: 5.3 ISSN: 0020-0255 CA: Q2 JCR: Q1 CCF-B |
|
38. | Fournier-Viger, P., Yang, P., Li, Z., Lin, J. C.-W., Kiran. R. U. (2019). Discovering Rare Correlated Periodic Patterns in Multiple Sequences. Data & Knowledge Engineering (DKE), 126: DOI: 101733, 10.1016/j.datak.2019.101733. |
ISI, EI, SCI |
|
39. | Fournier-Viger, P., Yang, P., Lin, J. C.-W, Duong, Q.-H., Dam, T.-L., Sevcik, L., Uhrin, D., Voznak, M. (2019). Discovering Periodic Itemsets using Novel Periodicity Measures. Advances in Electrical and Electronic Engineering, 17(1):33-44, DOI: 10.15598/aeee.v17i1.3185. | ISSN 1804-3119 corr. auth. |
|
40. | Luna, J. M., Fournier-Viger, P., Ventura, S.
(2019). Frequent Itemset Mining: a 25 Years Review. WIREs Data Mining and Knowledge Discovery, Wiley, 9(6):e1329. DOI: 10.1002/widm.1329 |
ISI, EI, SCI, Q1 IF: 4.703 ISSN: 1942-4787 CA: Q3 JCR: Q2 |
|
41. | Gan, W., Lin, J. C.-W., Fournier-Viger, P., Chao, H.-C., Yu, P. S. (2019). HUOPM: High Utility Occupancy Pattern Mining. IEEE Transactions on Cybernetics. IEEE. 50(3): 1195-1208. DOI: 10.1109/TCYB.2019.2896267 |
ISI, EI, SCI,
Q1 |
|
42. | Gan, W., Lin, J. C. W., Fournier-Viger, P., Chao, H.-C., Yu, P. S. (2019) A Survey of Parallel Sequential Pattern Mining. ACM Transactions on Knowledge Discovery from Data (TKDD), 13(3): 25:1-25:34. DOI: 10.1145/3314107 |
ISI, EI, SCI, |
|
43. | Chi, T. T., Duong, H., Le, B., Fournier-Viger, P. (2019). FMaxCloHUSM: An Efficient Algorithm for Mining Frequent Closed and Maximal High Utility Sequences. Engineering Applications of Artificial Intelligence (EAAI), Elsevier, 85: 1-20. DOI: 10.1016/j.engappai.2019.05.010 |
ISI, EI, SCI, SCR: Q1 IF: 2.819 ISSN: 0952-1976 CA: Q2 JCR: Q1 CCF-C |
|
44. | Lin, J. C.-W., Wu, J. M-T., Fournier-Viger, P., Chen, C.-H., Zhang, Y. (2019). A Sanitization Approach to Secure Shared Data in an IoT Environment. IEEE Access, 7: 25359-25368. DOI: 10.1109/access.2019.2899831 |
ISI, EI, SCI, SCR: Q2 IF: 4.098 ISSN: 2169-3536 CA: Q2 JCR: Q1 |
|
45. | Lin, J. C.-W., Zhang, S., Zhang, Y., Zhang, B., Fournier-Viger, P., Djenouri, Y. (2019). Hiding Sensitive Itemsets with Multiple Objective Optimization. Soft computing, Springer, 23 (23): 12779–12797. DOI: 10.1007/s0050 |
ISI, EI, SCI, Q3 IF: 2.367 ISSN: 1432-7643 CA: Q3 JCR: Q2 CCF-C |
|
46. | Amirat, H., Lagraa, N., Fournier-Viger, P., Ouinten, Y. (2019). NextRoute: A lossless model for accurate mobility prediction. Journal of Ambient Intelligence and Humanized Computing, Springer. (to appear) DOI: 10.1007/s12652-019-01327-w |
ISI, EI, SCI, Q2? |
|
47. | Win, K. N., Chen, J., Chen, Y., Fournier-Viger, P. (2019) PCPD: A Parallel Crime Pattern Discovery System for Large-scale Spatio-temporal Data based on Fuzzy Clustering. International Journal of Fuzzy Systems, Springer, 21(6):1961–1974. DOI: 10.1007/s40815-019-00673-3 |
ISI,EI, SCI IF: 2.396 ISSN: 1562-2479 CA: Q3 JCR: Q2 |
|
48. | Lin, J. C.-W., Li, T., Pirouz, M., Zhang, J., Fournier-Viger, P. (2019). High Average-Utility Sequential Pattern Mining based on Uncertain Databases. Knowledge and Information Systems (KAIS), Springer, 56(1): 165-196. DOI: 10.1007/s10115-019-01385-8 |
ISI, EI, SCI, Q2 IF: 2.39 ISSN:0219-1377 CA: Q3 JCR: Q2 CCF-B |
|
49. | Win, K. N., Li, K., Chen, J., Fournier-Viger, P., Li, K. (2019). Fingerprint Classification and Identification Algorithms for Criminal Investigation : A Survey. Future Generation Computer Systems, Elsevier, to appear. DOI: 10.1016/j.future.2019.10.019 |
ISI, EI, SCI, |
|
50. | Wu. J. M. T, Lin, J. C.-W., Fournier-Viger, P. Dj, Y., Chen, C.-H., Li, Z.(2019). Density-based Clustering Method for Privacy-Preserving Data Mining. Mathematical Biosciences and Engineering (MBE), 11 pages. DOI: ___ |
SCI, JCR Q3 |
|
2018 | 51. | Duong, H., Ramampiaro, H., Norvag, K., Fournier-Viger, P., Dam, T.-L. (2018). High Utility Drift Detection in Quantitative Data Streams. Knowledge-Based Systems (KBS), Elsevier, 157 (1): 34-51. DOI: 10.1016/j.knosys.2018.05.014 |
ISI, EI, SCI, Q1 IF: 5.3 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C |
52. | Gan, W., Lin, J. C.-W., Fournier-Viger, P., Chao, H.-C., Fujita, H. (2018). Extracting non-redundant correlated purchase behaviors by utility measure. Knowledge-Based Systems (KBS), Elsevier, 143: 30-41. |
ISI, EI, SCI, Q1 IF: 5.3 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C |
|
53. | Mafarja, M., Aljarah, I., Heidari, A. A., Faris, H., Fournier-Viger, P., Li, X., Mirjalili, S. (2018). Binary Dragonfly Optimization for Feature Selection using Time-Varying Transfer functions. Knowledge-Based Systems (KBS), Elsevier, 161(1): 185-204. |
ISI, EI, SCI, Q1 IF: 5.3 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C Web-of-Science Highly-Cited paper |
|
54. | Lin, C.-W., Ren, S., Fournier-Viger, P., Hong, T.-P. (2018). MEMU: More Efficient Algorithm to Mine High Average-Utility Patterns with Multiple Minimum Average-Utility Thresholds. IEEE Access, 6: 7593-7609. DOI: 10.1109/ACCESS.2018.2801261 |
ISI, EI, SCI, Q2 IF: 4.098 ISSN: 2169-3536 CA: Q2 JCR: Q1 |
|
55. | W. J. M. T., Lin, J.C.W. Pirouz, M., Fournier-Viger, P. (2018) TUB-HAUPM: Tighter Upper Bound for Mining High Average-Utility Patterns. IEEE Access 6: 18655-18669. DOI: 10.1109/ACCESS.2018.2820740 |
ISI, EI, SCI, Q2 IF: 4.098 ISSN: 2169-3536 CA: Q2 JCR: Q1 |
|
56. | Fournier-Viger, P., Zhang, Y., Lin, J. C.-W., Dinh, T., Le, B. (2018) Mining Correlated High-Utility Itemsets Using Various Correlation Measures. Logic Journal of the IGPL, Oxford Academic, 28(1): 19-32. [source
code] DOI: 10.1093/jigpal/jzz068 |
ISI, EI, SCI, IF: 0.575 ISSN:1367-0751 CA: Q4 JCR: Q3, corr. auth. |
|
57. | Zhang, B., Lin, J. C.-W., Fournier-Viger, P., Djenouri, Y. (2018) A (k, p)-anonymity Framework to Sanitize Transactional Database with Personalized Sensitivity. Journal of Internet Technology, Taiwan Academic Network (to appear). to appear. | ISI, EI, SCI, JCR Q3 IF: 0.715 ISSN:1607-9264 CA: Q4 JCR: JCR: Q4 |
|
58. | Dinh, D.-T., Le, B., Fournier-Viger, P., Huynh, V.-N. (2018) An efficient algorithm for mining periodic high-utility sequential patterns. Applied Intelligence, 48(12):4694-4714. |
ISI, EI, SCI, Q2 IF: 1.983 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C |
|
59. | Lin, J. C.-W., Shao, Y., Fournier-Viger, P., Djenouri, Y. (2018) Maintenance algorithm for high average-utility itemsets with transaction deletion. Applied Intelligence, 48(10): 3691-3706 DOI: 10.1007/s10489-018-1180-8 |
ISI, EI, SCI, Q2 IF: 1.983 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C |
|
60. | Le, T., Vo, B., Fournier-Viger, P., Lee, M. Y., Baik, S. W. (2018). SPPC: A New Tree Structure for Mining Erasable Patterns in Data Streams. Applied Intelligence, 459: 117-134. DOI: 10.1007/s10489-018-1280-5 |
ISI, EI, SCI, Q2 IF: 1.983 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C |
|
61. | Djenouri, Y., Djenourni, D., Belhadi, A., Fournier-Viger, P., Lin, J. C.-W. (2018) A New Framework for Metaheuristic-based Frequent Itemset Mining. Applied Intelligence, 48(12): 4775-4791 (2018) DOI: 10.1007/s10489-018-1245-8 |
ISI, EI, SCI, Q2 IF: 1.983 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C |
|
62. | Le, B. Dinh, D.-T., Huynh, N.V., Nguyen, Q. M., Fournier-Viger, P. (2018). An Efficient Algorithm for Hiding High Utility Sequential Patterns. International Journal of Approximate Reasoning, Elsevier, 95: 77-92. DOI: 10.1016/j.ijar.2018.01.005 |
ISI, EI, SCI, IF: 2.845 ISSN: 0888-613X CA: Q3 JCR: Q2 CCF-B |
|
63. | Lin, J. C.-W., Ren, S.-F., Fournier-Viger, P., Pan, J.-S., Hong, T.-P. (2018). Efficiently Updating the Discovered High Average-Utility Itemsets with Transaction Insertion. Engineering Applications of Artificial Intelligence (EAAI), Elsevier, 72: 136-149. DOI: 10.1016/j.engappai.2018.03.021 |
ISI, EI, SCI, Q1 IF: 2.819 ISSN: 0952-1976 CA: Q2 JCR: Q1 CCF-C |
|
64. | Djenouri, Y., Belhadi, A, Fournier-Viger, P., Fujita, H. (2018) Mining Diversified Association Rules in Big Datasets: a Cluster/GPU/Genetic Approach. Information Sciences, Elsevier, to appear. DOI: 10.1016/j.ins.2018.05.031 |
ISI, EI, SCI, IF: 4.305 ISSN: 0020-0255 CA: Q2 JCR: Q1 CCF-B |
|
65. | Djenouri, Y., Belhadi, A, Fournier-Viger, P., Lin, J. C.-W. (2018) Fast and Effective Cluster-based Information Retrieval using Frequent Closed Itemsets. Information Sciences, Elsevier, 453: 154-167. DOI: 10.1016/j.ins.2018.04.008 |
ISI, EI, SCI, Q1 IF: 4.305 ISSN:0020-0255 CA: Q2 JCR: Q1 CCF-B |
|
66. | Djenouri, Y., Djenouri, D., Belhadi, A, Fournier-Viger, P., Lin, J. C.-W., Bendjoudi, A. (2018) Exploiting GPU parallelism in improving bee swarm optimization for mining big transactional databases. Information Sciences, Elsevier, 496: 326-342. DOI: 10.1016/j.ins.2018.06.060 |
ISI, EI, SCI, Q1 IF: 4.305 ISSN:0020-0255 CA: Q2 JCR: Q1 CCF-B |
|
67. | Lin, J.-C.W., Yang, L., Fournier-Viger, P., Hong, T.-P. (2018). Mining of Skyline Patterns by Considering both Frequent and Utility Constraints. Engineering Applications of Artificial Intelligence, Elsevier, 77: 229-238. DOI: 10.1016/j.engappai.2018.10.010 |
ISI, EI, SCI, Q1 * Best theory award EAAI / IFAC 2020* |
|
68. | Lin, J.-C.W., Zhang, Y., Fournier-Viger, P., Hong, T.-P. (2018) Efficiently Updating the Discovered Multiple Fuzzy Frequent Itemsets with Transaction Insertion, International Journal of Fuzzy Systems, Springer, 20(8):2440–2457. DOI: 10.1007/s40815-018-0520-5 |
ISI, EI, SCI IF: 2.19 ISSN: 1562-2479 CA: Q3 JCR: Q2 |
|
69. | Djenouri, Y., Djenouri, D., Belhadi, A, Fournier-Viger, P., Lin, J. C.-W., (2018). GPU-based Swarm Intelligence for Association Rule Mining in Big Databases. Intelligent Data Analysis, IOS Press, 23(1): 57-76. DOI: 10.3233/IDA-173785 |
ISI, EI, SCI, IF: 0.612 ISSN 1088-467X CA: Q4 JCR: Q4 CCF-C |
|
2017 | 70. | Gan, W., Lin, J. C.-W., Fournier-Viger, P., Chao, H.-C., Hong, T.-P., Fujita, H.
(2017). Incremental High-Utility Itemset Mining: A Survey. WIREs Data Mining and Knowledge Discovery, Wiley, to appear. DOI: 10.1002/widm.1242 |
ISI, EI, SCI, Q1 ISSN: 1942-4787 CA: Q3 JCR: Q2 |
71. | Fournier-Viger, P., Lin, J. C.-W., Vo, B, Chi, T.T., Zhang, J., Le, H. B. (2017). A Survey of Itemset Mining. WIREs Data Mining and Knowledge Discovery, Wiley, e1207 doi: 10.1002/widm.1207, 18 pages. | ISI, EI, SCI, Q1 ISSN: 1942-4787 CA: Q3 JCR: Q2, corr. auth. |
|
72. | Fournier-Viger, P., Lin, J. C.-W., Kiran, R. U., Koh, Y. S., Thomas, R. (2017). A Survey of Sequential Pattern Mining. Data Science and Pattern Recognition (DSPR), vol. 1(1), pp. 54-77. | ISSN: 2520-4165, corr. auth. | |
73. | Lin, J. C. W, Ren, S., Fournier-Viger, P. Hong, T.-P., Su, J.-W., Vo, B.
(2017). A Fast Algorithm for Mining High Average-Utility Itemsets. Applied Intelligence, Springer, 47:331-347. DOI: 10.1007/s10489-017-0896-1 |
ISI, EI, SCI, Q2 IF: 1.983 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C |
|
74. | Bouakkaz, M., Ouinten, Y., Loudcher, S., Fournier-Viger, P.
(2017). Efficiently mining frequent itemsets applied for textual aggregation. Applied Intelligence, Springer, 48(4):1013-1019). DOI: 10.1007/s10489-017-1050-9 |
ISI, EI, SCI, Q2 IF: 1.983 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C |
|
75. | Nguyen, L. T. T., Vo, B., Nguyen, L. T. T., Fournier-Viger, P., Selamat, A.
(2017). ETARM: an efficient top-k association rule mining algorithm. Applied Intelligence, Springer, vol. 48, no. 5, 1148-1160. DOI: 10.1007/s10489-017-1047-4 |
ISI, EI, SCI, Q2 IF: 1.983 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C |
|
76. | Duong, Q.H., Fournier-Viger, P., Ramampiaro, H., Norvag, K. Dam, T.-L.
(2017).
DOI: 10.1007/s10489-017-1057-2 |
ISI, EI, SCI, Q2 IF: 1.983 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C, corr. auth. |
|
77. | Zhang, J., Zhu, X., Fournier-Viger, P., Lin, J. C.-W. (2017). FRIOD: A Deeply Integrated Feature-Rich Interactive System for Effective and Efficient Outlier Detection,. IEEE Access (to appear) DOI: 10.1109/ACCESS.2017.2771237 |
ISI, EI, SCI, Q2 IF: 4.098 ISSN: 2169-3536 CA: Q2 JCR: Q1 |
|
78. | Lin, C.-W., Ren, S., Fournier-Viger, P., Hong, T.-P. (2017). EHAUPM: Efficient High Average-Utility Pattern Mining with
Tighter Upper-Bounds. IEEE Access, 5: 12927-12940. |
ISI, EI, SCI, Q2 IF: 4.098 ISSN: 2169-3536 CA: Q2 JCR: Q1 |
|
79. | Lin, C.-W., Liu, Q., Fournier-Viger, P., Hong, T.-P. (2017). PTA: An Efficient System for Transaction Database Anonymization . IEEE Access, vol. 4, pp. 6467-6479, IEEE. DOI: 10.1109/ACCESS.2016.2596542 |
ISI, EI, SCI, Q2 IF: 4.098 ISSN: 2169-3536 CA: Q2 JCR: Q1 |
|
80. | Djenouri, Y., Habbas, Z., Djenouri, D., Fournier-Viger, P. (2017). Bee Swarm Optimization For Solving MAXSAT Problem Using Prior Knowledge.
Soft Computing, Springer, 496: 326-342. DOI: 10.1007/s00500-017-2956-1 |
ISI, EI, SCI, Q3 IF: 2.784 ISSN: 1432-7643 CA: Q3 JCR: Q2 CCF-C |
|
81. | Djenouri, Y., Belhadi, A., Fournier-Viger, P. Extracting Useful Knowledge from Event Logs: A Frequent Itemset Mining Approach (2017). Knowledge-Based Systems (KBS), Elsevier,139: 132-148. DOI: 10.1016/j.knosys.2017.10.016 |
ISI, EI, SCI, Q1 IF: 4.396 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C, corr. auth. |
|
82. | Lin, J. C.-W., Gan, W., Fournier-Viger, P., Chao, H.-C., Wu. J. T., Zhan, J.
(2017). Extracting Recent Weighted-based Patterns from Uncertain Temporal Databases. Engineering Applications of Artificial Intelligence, Elsevier, 61, pp. 161-172 DOI: 10.1016/j.engappai.2017.03.004 |
ISI, EI, SCI, Q1 IF: 2.819 ISSN: 0952-1976 CA: Q2 JCR: Q1 CCF-C |
|
83. | Lin, J. C.-W., Gan, W., Fournier-Viger, P., Chao, H.-C., Zhan, J.
(2017). Mining of Frequent Patterns with Multiple Minimum Supports. Engineering Applications of Artificial Intelligence, Elsevier, 60:83-96. DOI: 10.1016/j.engappai.2017.01.009 |
ISI, EI, SCI, Q1 IF: 2.819 ISSN: 0952-1976 CA: Q2 JCR: Q1 CCF-C |
|
84. | Gan, W., Lin, J. C.-W., Fournier-Viger, P., Chao, H.-C., Zhan, J., Zhang, J. (2017). Exploiting highly qualified pattern with frequency
and weight occupancy. Knowledge and Information Systems (KAIS), Springer, 56(1): 165-196. DOI: 10.1007/s10115-017-1103-8 |
ISI, EI, SCI, Q2 IF: 2.247 ISSN:0219-1377 CA: Q3 JCR: Q2 CCF-B |
|
85. | Le, B., Duong, H., Truong, T., Fournier-Viger, P. (2017). FCloSM, FGenSM: Two New Algorithms for Efficiently Mining Frequent Closed and Generator Sequences using Local Pruning Strategy. Knowledge and Information Systems (KAIS), Springer, 53(1):71-107. DOI: 10.1007/s10115-017-1032-6 |
ISI, EI, SCI, Q2 IF: 2.247 ISSN:0219-1377 CA: Q3 JCR: Q2 CCF-B |
|
86. | Dam, T.-L., Li, K., Fournier-Viger, P., Duong, H.
(2017). An efficient algorithm for mining top-k on-shelf high utility itemsets. Knowledge and Information Systems (KAIS), Springer, 62:621-655. DOI: 10.1007/s10115-016-1020-2 |
ISI, EI, SCI, Q2 IF: 2.247 ISSN:0219-1377 CA: Q3 JCR: Q2 CCF-B |
|
87. | Zida, S., Fournier-Viger, P., Lin, J. C.-W., Wu, C.-W., Tseng, V.-S. (2017). EFIM: A Fast and Memory Efficient Algorithm for High-Utility Itemset Mining . Knowledge and Information Systems (KAIS), Springer, 51(2), 595-625 [powerpoint] [source
code] DOI: 10.1007/s10115-016-0986-0 |
ISI, EI, SCI, Q2 IF: 2.247 ISSN:0219-1377 CA: Q3 JCR: Q2 CCF-B, corr. auth. |
|
88. | Lin, J. C., Hong, T.-P., Fournier-Viger, P., Liu, Q., Wong, J.-W., Zhan, J. (2017). Efficient Hiding of Confidential High-Utility Itemsets with Minimal Side Effects.. Journal of Theoretical and Experimental Artificial Intelligence, Taylor and Francis (to appear) DOI: 10.1080/0952813X.2017.1328462 |
ISI, EI, SCI, Q2 IF:_ ISSN: 2169-3536 __________ |
|
89. | Dam, T.-L., Li, K., Fournier-Viger, P., Duong, H.
(2017). CLS-Miner: Efficient and Effective Closed High utility Itemset Mining. Frontiers of Computer Science, Springer (to appear), 13(2): 357-381 DOI: 10.1007/s1170 |
ISI, EI, SCI, Q2 IF: 1.105 ISSN: 2095-2228 CA: Q4 JCR: Q3 CCF-C |
|
90. | Lin, J. C.-W., Zhang, J. Fournier-Viger, P., Hong, T.-P.(2017). A Two-Phase Approach to Mine Short-Periodic High Utility Itemsets in Transactional Databases.
Advanced Engineering Informatics, Elsevier, 33, 29-43. DOI: 10.1016/j.aei.2017.04.007 |
ISI, EI, SCI, Q1 ISSN: 1474-0346 CA: Q2 JCR: Q2 CCF-B |
|
91. | Amirat, H., Lagraa, N., Fournier-Viger, P., Ouinten, Y. (2017). MyRoute: a Graph-dependency Based Model for Real-time Route Prediction. Journal of Communications, Engineering and Technology Publishing, vol. 12, no. 12, 668-676. 10.12720/jcm.12.12.668-676 DOI: 10.12720/jcm.12.12.668-676. |
ISI, EI, SCI, Q4 IF: ISSN: 1796-2021 ----------- |
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92. | Lin, J. C.-W., Li, T., Fournier-Viger, P., Zhang, J. (2017). Mining of High Average-Utility Patterns with Item-Level Thresholds. Journal of Internet Technology, Taiwan Academic Network (to appear). DOI: |
ISI, EI, SCI, JCR Q3 IF: 0.715 ISSN:1607-9264 CA: Q4 JCR: Q4 |
|
93. | Zhang, B., Lin, J. C.-W., Li, T., Gan, W., Fournier-Viger, P.
(2017). Mining High Utility-Probability Sequential Patterns in Uncertain Databases. PLoS One, Public Library of Science, to appear. DOI: 10.1371/journal.pone.0180931 |
ISI, EI, SCI, Q1 IF: ISSN: 1932-6203 |
|
94. | Mustafa, R. U., Nawaz, M. S., Ferzund, J., Lali, M. I. U., Shazad, B., Fournier-Viger, P. (2017). Early Detection of Controversial Urdu Speeches from Social Media. Data Science and Pattern Recognition (DSPR), vol. 1(2), 26-42. | ISSN: 2520-4165 | |
2016 | 95. | Tseng, V., Wu, C., Fournier-Viger, P., Yu, P. S. (2016). Efficient
Algorithms for Mining Top-K High Utility Itemsets. IEEE
Transactions on Knowledge and Data Engineering (TKDE), 28(1): 54-67. [source
code] |
ISI, EI, SCI, Q1 IF: 2.07 ISSN: 1041-4347 CA: Q2 JCR: Q1 CCF-A |
96. | Dougnon, Y. R., Fournier-Viger, P., Lin, J. C.-W., Nkambou, R. (2016). Inferring Social Network User Profiles using a Partial Social Graph. Journal of Intelligent Information Systems (JIIS), Springer, 47(2): 313-344. DOI: 10.1007/s10844-016-0402-y |
ISI, EI, SCI, Q4 IF: 1.294 ISSN: 0925-9902 CA: Q4 JCR: Q3 CCF-C, corr. auth. |
|
97. | Lin, J. C.-W., Gan, W., Fournier-Viger, P., Hong, T.-P. Chao, H.-C. (2016). FDHUP: Fast Algorithm for Mining Discriminative High Utility Patterns . Knowledge and Information Systems (KAIS), Springer, June 2017, Volume 51, Issue 3, 873-909 DOI: 10.1007/s10115-016-0991-3 |
ISI, EI, SCI, Q2 IF: 2.004 ISSN:0219-1377 CA: Q3 JCR: Q2 CCF-B |
|
98. | Lin, J. C.-W., Gan, W., Fournier-Viger, P., Hong, T.-P., Tseng, V. S. (2016). Efficiently Mining Uncertain High-Utility Itemsets.
Soft Computing, Springer, 21:2801-2820. DOI: 10.1007/s00500-016-2159-1 |
ISI, EI, SCI, Q3 IF: 2.472 ISSN: 1432-7643 CA: Q3 JCR: Q2 CCF-C |
|
99. | Lin, J. C.-W., Yang, L., Fournier-Viger, P., Hong, T.-P., Voznak, M. (2016). A binary PSO approach to mine high-utility itemsets.
Soft Computing, Springer. 21(17): 5103-5121 DOI: 10.1007/s00500-016-2106-1 |
ISI, EI, SCI, Q3 IF: 2.472 ISSN: 1432-7643 CA: Q3 JCR: Q2 CCF-C |
|
100. | Dam, T.-L., Li, K. , Fournier-Viger, P. (2016). Chemical reaction optimization with unified tabu search for the vehicle routing problem. Soft Computing, Springer, 21(21): 6421-6433 DOI: 10.1007/s00500-016-2200-4 |
ISI, EI, SCI, Q3 IF: 2.472 ISSN: 1432-7643 CA: Q3 JCR: Q2 CCF-C |
|
101. | Lin, J. C.-W., Liu, Q., Fournier-Viger, P., Hong, T.-P., Voznak, M., Zhan, J. (2016). A Sanitization Approach For Hiding Sensitive Itemsets Based On Particle Swarm Optimization.
Engineering Applications of Artificial Intelligence, 53:1-18. DOI: 10.1016/j.engappai.2016.03.007 |
ISI, EI, SCI Q2 IF: 2.894 ISSN: 0952-1976 CA: Q2 JCR: Q1 CCF-C |
|
102. | Lin, J. C.-W., Li, T., Fournier-Viger, P., Hong, T.-P., Voznak, M., Zhan, J. (2016). An Efficient Algorithm to Mine High Average-Utility Itemsets.
Advanced Engineering Informatics, Elsevier, 30(2): 233-243. DOI: 10.1016/j.aei.2016.04.002 |
ISI, EI, SCI, Q1 IF: 2.68 ISSN: 1474-0346 CA: Q2 JCR: Q2 CCF-B |
|
103. | Lin, J. C. W., Gan, W., Fournier-Viger, P., Hong, T. P., Tseng, V. S. (2016). Weighted frequent itemset mining
over uncertain databases. Applied Intelligence, 44:232-250. DOI: 10.1007/s10489-015-0703-9 |
ISI, EI, SCI, Q2 IF: 1.904 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C |
|
104. | Dam, T.-L., Li, K., Fournier-Viger, P. (2016). An
efficient algorithm for mining top-rank-k frequent patterns.
Applied Intelligence, Springer, 45(1): 96-111. DOI: 10.1007/s10489-015-0748-9 |
ISI, EI, SCI, Q2 ISSN: 0924-669X CA: Q3 JCR: Q2 CCF-C |
|
105. | Lin, J. C. W., Gan, W., Fournier-Viger, P., Hong, T. P., Tseng, V. S. (2016). Fast Algorithms for Mining High-Utility Itemsets with Various Discount Strategies. Advanced Engineering Informatics, 30(2): 109-126. DOI: 10.1016/j.aei.2016.02.003 |
ISI, EI, SCI, Q1 IF: 2.68 ISSN: 1474-0346 CA: Q2 JCR: Q2 CCF-B |
|
106. | Lin, J. C. W., Fournier-Viger, Gan, W. (2016). FHN: An Efficient Algorithm for Mining High-Utility Itemsets with Negative Unit Profits. Knowledge-Based Systems (KBS), Elsevier, 111(1):283-298 DOI: 10.1016/j.knosys.2016.08.022 |
ISI, EI, SCI, Q1 IF: 4.529 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C, corr. auth. |
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107. | Lin, J. C.-W., Gan, W., Fournier-Viger, P., Hong, T.-P., Zhan, J. (2016). Efficient Mining of High-Utility Itemsets Using Multiple Minimum Utility Thresholds. Knowledge-Based Systems (KBS), Elsevier, 113:100-115. DOI: 10.1016/j.knosys.2016.09.013 |
ISI, EI, SCI, Q1 IF: 4.529 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C |
|
108. | Duong, Q.-H., Liao, B., Fournier-Viger, P., Dam, T.-L. (2016). An efficient algorithm for mining the top-k high utility itemsets, using novel threshold raising and pruning strategies. Knowledge-Based Systems (KBS), Elsevier, 104:106-122. DOI: 10.1016/j.knosys.2016.04.016 |
ISI, EI, SCI, Q1 IF: 4.529 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C |
|
109. | Lin., J. C. W., Gan. W., Fournier-Viger, P., Tseng, V. S. (2016). Efficient Algorithms for Mining High-Utility Itemsets in Uncertain Databases. Knowledge-Based Systems (KBS), Elsevier, 96, 171-187. |
ISI, EI, SCI, Q1 IF: 4.529 ISSN: 0950-7051 CA: Q2 JCR: Q1 CCF-C |
|
110. | Lin., J. C. W., Gan. W., Fournier-Viger, P., Hong, T. P. (2016). Efficiently Updating the Discovered Sequential Patterns for Sequence Modification. Int'l Journal of Software Engineering and Knowledge Engineering (IJSEKE), 26(8), pp 1285-1313. DOI: 10.1142/S0218194016500455 |
EI, SCI, Q4 IF: 4.529 ISSN: 0218-1940 CA: Q4 ________ CCF-C |
|
2015 | 111. | Fournier-Viger, P., Wu, C.-W., Tseng, V.S., Cao, L., Nkambou, R. (2015). Mining Partially-Ordered Sequential Rules Common to Multiple Sequences. IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(8): 2203-2216. [source code] | ISI, EI SCI, Q1 IF: 2.07 ISSN: 1041-4347 CCF-A, corr. auth. |
112. | Tseng, V., Wu, C., Fournier-Viger, P., Yu, P. S. (2015). Efficient Algorithms for Mining the Concise and Lossless Representation of Closed+ High Utility Itemsets. IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(3): 726-739. [source code] | ISI, EI, SCI, Q1 IF: 2.07 ISSN: 1041-4347 CCF-A |
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113. | Lin., J. C. W., Yang, L., Fournier-Viger, Frnda, J., Sevcik, L., Voznak, M. (2015). An Evolutionary Algorithm to Mine High-Utility Itemsets. Advances in Electrical and Electronic Engineering, Vol. 13, No.5., pp. 392-398. | ISI, EI, SCI, Q4 ISSN: 1582-7445 CCF-B |
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114. | Lin, J. C. W., Tin, L., Fournier-Viger, P., Hong, T. P. (2015). A fast Algorithm for mining fuzzy frequent itemsets. Journal of Intelligent and Fuzzy Systems, 29(6), 2373-2379. | ISI, EI, SCI, Q4 IF: 1.81 ISSN: 1064-1246 |
|
115. | Lin, J. C., Gan, W., Fournier-Viger, P., Hong, T.-P. (2015). RWFIM: Recent Weighted-Frequent Itemsets Mining. Engineering Applications of Artificial Intelligence, Elsevier, 45, 18-32. | ISI, EI, SCI, Q2 IF: 2.21 ISSN: 0952-1976 CA: Q2 JCR: Q1 CCF-C |
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2014 | 116. | Fournier-Viger, P., Gomariz, A., Gueniche, T., Soltani, A., Wu., C., Tseng, V. S. (2014). SPMF: a Java Open-Source Pattern Mining Library. Journal of Machine Learning Research (JMLR), 15: 3389-3393. | ISI, EI SCI, Q1 IF: 2.47 ISSN: 1532-4435 CCF-A, corr. auth. |
2013 | 117. | Fournier-Viger, P., Nkambou, R., Mephu Nguifo, E., Mayers, A., Faghihi, U. (2013). A Multi-Paradigm Intelligent Tutoring System for Robotic Arm Training. IEEE Transactions on Learning Technologies (TLT), 6(4): 364-377. | ISI, EI, SSCI, Q4 IF: 1.22 ISSN: 1939-1382, corr. auth. |
2012 | 118. | Fournier-Viger, P., Faghihi, U., Nkambou, R., Mephu Nguifo, E. (2012). CMRules: Mining Sequential Rules Common to Several Sequences. Knowledge-based Systems, Elsevier, 25(1): 63-76. [source code] | ISI, EI, SCI, Q1 IF: 4.104 ISSN: 0950-7051 CCF-C |
119. | Faghihi, U., P. Fournier-Viger, Nkambou, R. (2012). A Computational Model for Causal Learning in Cognitive Agents, Knowledge-Based Systems, Elsevier, 30, 48-56 | ISI, EI, SCI, Q1 IF: 4.104 ISSN: 0950-7051 CCF-C |
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2011 | 120. | Faghihi, U., Poirier, P., Fournier-Viger, P., Nkambou, R. (2011). Human-Like Learning in a Cognitive Agent. Journal of Experimental & Theoretical Artificial Intelligence, Taylor & Francis, 23(4): 497-528. | ISI, EI, SCI, Q4 IF: 0.33 ISSN: ISSN: 2169-3536 |
121. | Nkambou, R., Fournier-Viger, P., Mephu Nguifo, E. (2011). Learning Task Models in Ill-defined Domain Using an Hybrid Knowledge Discovery Framework. Knowledge-Based Systems, Elsevier, 24(1):176-185. | ISI, EI, SCI, Q1 IF: 2.42 CCF-C |
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<2010 | 122. | Fournier-Viger, P., Faghihi, U., Nkambou, R.,
Mephu Nguifo, E. (2010). Exploiting Sequential
Patterns Found in Users’ Solutions and Virtual Tutor Behavior to
Improve Assistance in ITS. Educational Technology &
Society, 13(1):12-24. DOI: |
SSCI IF: 1.34 ISSN: 1436-4522, corr. auth. |
123. | Nkambou, R, Fournier-Viger, P., Mephu Nguifo, E.
(2009). Improving the Behavior of Intelligent Tutoring
Agents with Data Mining. IEEE Intelligent Systems, 24(3):46-53. DOI: 10.1109/MIS.2009.59 |
ISI, EI, SCI, Q2 IF: 3.14 ISSN: 1541-1672 |
|
124. | Fournier-Viger, P., Nkambou, R., Mayers, A.
(2008). Evaluating
Spatial
Representations and Skills in a Simulator-Based Tutoring System.
IEEE Transactions on Learning Technologies (TLT), 1(1):63-74. DOI: 10.1109/TLT.2008.13 |
ISI, EI, SSCI IF: 0.82 ISSN: 1939-1382, corr. auth. |
|
125. | Fournier-Viger, P., Najjar, M., Mayers, A.,
Nkambou, R. (2006). A Cognitive and Logic based Model for
Building Glass-box Learning Objects. Interdisciplinary Journal of e-Skills and Lifelong Learning, 2:77-94. DOI: 10.28945/402 |
IF: 22 ISSN: 2375-2084, corr. auth. |
2021 | 1. | Fournier-Viger, P., Chen, Y., Nouioua, F., Lin, J. C.-W. (2020). Mining Partially-Ordered Episode Rules in an Event Sequence. Proc. of the 13th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2021), Springer LNAI, 12 pages, to appear. | EI, corr. auth. |
2. | Nawaz, M. S., Fournier-Viger, P., Song, W., Lin, J. C.-W., Noack, B. (2020). Investigating Crossover Operators in Genetic Algorithms for High-Utility Itemset Mining. Proc. of the 13th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2021), Springer LNAI, 12 pages, to appear. | EI, corr. auth. | |
2020 | 3. | Fournier-Viger, P., He, G., Lin, J. C.-W., Gomes, H. M. (2020). Mining Attribute Evolution Rules in Dynamic Attributed Graphs. Proc. 22nd Intern. Conf. on Data Warehousing and Knowledge Discovery (DAWAK 2020), Springer, pp. 167-182. [ppt] DOI: 10.1007/978-3-030-59065-9_14 |
EI, corr. auth. |
4. | Nawaz, M. Z., Hasan, O., Nawaz, S., Fournier-Viger, P., Sun, M.
(2020). Proof Searching in HOL4 with Genetic Algorithm. Proc. 35th Symposium on Applied Computing (ACM SAC 2020). ACM Press, pp. 513-520. DOI: 10.1145/3341105.3373917 |
EI | |
5. | Fournier-Viger, P., Yang, Y., Lin, J. C.W., Frnda, J. (2020). Mining Locally Trending High Utility Itemsets. Proc. 24th Pacific-Asia Conf. Knowledge Discovery and Data Mining (PAKDD 2020), Springer, LNAI, pp.99-111. [video] [ppt] DOI: 10.1007/978-3-030-47436-2_8 |
EI accept. rate: 21 % CCF-C, corr. auth. |
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6. | Fournier-Viger, P., Wang, Y., Yang, P., Lin, J. C.-W., Yun, U. (2020). TKE: Mining Top-K Frequent Episodes. Proc. 33rd Intern. Conf. on Industrial, Engineering and Other
Applications of Applied Intelligent Systems (IEA AIE 2020), Springer LNCS , pp. 832-845. [source code] [ppt] DOI: 10.1007/978-3-030-55789-8_71 |
EI, corr. auth. | |
7. | Fournier-Viger, P., Yang, Y., Lin, J. C.-W., Luna, J. M., Ventura, S. (2020). Mining Cross-Level High Utility Itemsets. Proc. 33rd Intern. Conf. on Industrial, Engineering and Other
Applications of Applied Intelligent Systems (IEA AIE 2020), Springer LNAI, pp. 858-871. [ppt] DOI: 10.1007/978-3-030-55789-8_73 |
EI, corr. auth. | |
8. | Wu, J.-T., Lin, J C.-W. , Fournier-Viger, P., Cheng, C.-F. (2020). Maintenance of Prelarge High Average-Utility Patterns in Incremental Databases. Proc. 33rd Intern. Conf. on Industrial, Engineering and Other
Applications of Applied Intelligent Systems (IEA AIE 2020), Springer LNAI, pp. 884-898. DOI: 10.1007/978-3-030-55789-8_75 |
EI | |
9. | Zheng, Y., Niu, X., Fournier-Viger, P., Li, F., Gao, L. (2020). Distributed Density Peak Clustering of Trajectory Data on Spark. Proc. 33rd Intern. Conf. on Industrial, Engineering and Other
Applications of Applied Intelligent Systems (IEA AIE 2020), Springer LNAI, pp. 792-806. DOI: 10.1007/978-3-030-55789-8_68 |
EI | |
10. | Win, K., Chen, J., Mingxin, D., Xiao, G., Li, K., Fournier-Viger, P. (2020). A Decision Support System to Provide Criminal Pattern Based Suggestions to Travelers. Proc. 33rd Intern. Conf. on Industrial, Engineering and Other
Applications of Applied Intelligent Systems (IEA AIE 2020), Springer LNAI, pp. 582-587. DOI: 10.1007/978-3-030-55789-8_50 |
EI | |
11. | Wu. C.-W., Hang, T.-Z., Fournier-Viger, P., Chen, M.-T., Lin, Y.-W. (2020). An Efficient Conversation Group Inference System based on Keywords. Proceedings of 25th International Computer Symposium (ICS 2020). IEEE, to appear. | EI | |
12. | Kiran, R. U., Srivasthava, S., Fournier-Viger, P., Zettsu, K., Toyoda, M., Kitsuregawa, M. (2020). Discovering Frequent Neighborhood Patterns in Very Large Spatiotemporal Databases. Proc. ACM 28th Intern. Conf. on Advances in Geographic Information Systems (SIGSPATIAL 2020), to appear. DOI: |
EI | |
2019 | 13. | Fournier-Viger, P., Li, J., Lin, J. C.-W., Chi, T.T. (2019). Discovering and Visualizing Patterns in Cost/Utility Sequences. Proc. 21st Intern. Conf. on Data Warehousing and Knowledge Discovery (DAWAK 2019), Springer, pp. 73-88. DOI: 10.1007/978-3-030-27520-4_6 [source code] |
EI, corr. auth. |
14. | Fournier-Viger, P., Cheng, C., Cheng, Z., Lin, J. C.-W., Selmaoui-Folcher, N. (2019). Finding Strongly Correlated Trends in Dynamic Attributed Graphs. Proc. 21st Intern. Conf. on Data Warehousing and Knowledge Discovery (DAWAK 2019), Springer, pp. 250-265. [ppt] DOI: 10.1007/978-3-030-27520-4_18 |
EI, corr. auth. | |
15. | Gomez, H. M., Bifet, A., Fournier-Viger, P., Granatyr, J., Read, J. (2019). Network of Experts: Learning from evolving data streams through network-based ensembles. Proc. 26th International Conference on Neural Information Processing (ICONIP 2019). Springer, LNCS 11953, pp. 704–716, DOI: 10.1007/978-3-030-36708-4_58 |
EI CCF-C |
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16. | Ktistakis, R., Fournier-Viger, P., Puglisi, S., Raman, R. (2019). Succinct BWT-based Sequence prediction. Proc. 30th International Conference on Database and Expert Systems Applications (DEXA 2019), Springer, pp. 91-10. DOI: 10.1007/978-3-030-27618-8_7 [ C++ implementation with Python wrapper (unofficial)] [datasets] |
EI accept. rate: 20% CCF-C |
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17. | Kiran, U., Reddy, T. Y., Fournier-Viger, P., Toyoda, M., Reddy, P. K., Kitsuregawa, M. (2019). Efficiently Finding High Utility-Frequent Itemsets using Cutoff and Suffix Utility. Proc. 23nd Pacific-Asia Conf. Knowledge Discovery and Data Mining (PAKDD 2019), Springer, LNAI, pp. 191-203. |
EI accept. rate: 24.7 % CCF-C |
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18. | Fournier-Viger, P., Cheng, C., Lin, J. C.-W., Yun, U., Kiran, U. (2019). TKG: Efficient Mining of Top-K Frequent Subgraphs. Proc. of 7th Intern. Conf. on Big Data Analytics (BDA 2019), Springer, 20 pages, pp. 209-226. [ppt] [source code] DOI: 10.1007/978-3-030-37188-3_13 |
EI accept. rate: 25%, corr. auth. |
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19. | Duong, H., Truong, T., Le, B., Fournier-Viger, P. (2019). An Explicit Relationship between Sequential Patterns and their Concise Representations. Proc. of 7th Intern. Conf. on Big Data Analytics (BDA 2019), Springer, pp. 341-361. DOI: 10.1007/978-3-030-37188-3_20 |
EI accept. rate: 25% |
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20. | Fournier-Viger, P., Yang, P., Lin, J. C.-W., Yun, U. (2019). HUE-SPAN: Fast High Utility Episode Mining. Proc. 14th Intern. Conference on Advanced Data Mining and Applications
(ADMA 2019) Springer LNAI, pp. 169-184. [ppt] [source code] DOI: 10.1007/978-3-030-35231-8_12 |
EI accept. rate: 23%, corr. auth. |
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21. | Tang, F., Tse, D., Huang, D. T. J., Koh, Y. S., Fournier-Viger, P. (2019). Adaptive Self-Sufficient Itemset Miner for Transactional Data Streams. Proc. 16th Pacific Rim Intern. Conf on Artificial Intelligence (PRICAI-2019), Springer LNCS, to appear. DOI: 10.1007/978-3-030-29911-8_32 |
EI CCF-C |
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22. | Fournier-Viger, P., Yang, P., Lin, J. C.-W., Kiran, U. (2019). Discovering Stable Periodic-Frequent Patterns in Transactional Data. Proc. 32nd Intern. Conf. on Industrial, Engineering and Other
Applications of Applied Intelligent Systems (IEA AIE 2019), Springer LNAI, pp. 230-244. [ppt] [source code] [video] DOI: 10.1007/978-3-030-22999-3_21 |
EI * Best paper award* corr. auth. |
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23. | Lin, J. C.-W., Wu, J. M.T., Fournier-Viger, P., Hong, T.P., Ting, L. (2019). Efficient Mining of High Average-Utility Sequential Patterns from Uncertain Databases. Proc. 2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2019), IEEE, pp. 1989-1994. DOI: 10.1109/SMC.2019.8914546 |
EI CCF-C |
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24. | Kiran, U., Zettsu, K., Toyoda, M., Fournier-Viger, P., Reddy, P. R., Kitsuregawa, M. (2019). Discovering Spatial High Utility Itemsets in Spatiotemporal Databases. Proc. of 31st Intern. Conf. on Scientific and Statistical Database Management (SSDBM 2019), ACM, pp. 49-60 DOI: 10.1145/3335783.3335789 |
EI CCF-C |
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25. | Wu, J. W.M., Lin, J. C. W., Fournier-Viger, P., Wiktorski, T., Hong, T.P. (2019). A GA-based Framework for Mining High Fuzzy Utility Itemsets. Proc. IEEE BigData 2019, IEEE, pp. 2708-2715. DOI: 10.1109/BigData47090.2019.9006171 |
EI accept. rate: 19% |
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26. | Lin, J. C. W., Li, Y., Fournier-Viger, P., Djenouri, Y., Wang, S.-L. (2019). Mining High-Utility Sequential Patterns from Big Datasets. Proc. IEEE BigData 2019, IEEE, pp. 2674-2680. DOI: 10.1109/BigData47090.2019.9005996 |
EI accept. rate: 19% |
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27. | Win, K. N., Chen, J., Xiao, G., Chen, Y., Fournier-Viger (2019) A Parallel Crime Activity Clustering Algorithm based on Apache Spark Cloud Computing Platform. Proc. of 21st IEEE Conferences on High Performance Computing and Communications (HPCC-2019).pp. 68-74. DOI: 10.1109/HPCC/SmartCity/DSS.2019.00025 |
EI CCF-C |
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28. | Wu, J. M.-T., Lin, J. C.-W., Fournier-Viger, P., Chen, C.-H., Zhang, Y. et al. (2019). A Swarm-based Data Sanitization Algorithm in Privacy-Preserving Data Mining. Proc. of 2019 IEEE Congress on Evolutionary Computation (IEEE CEC 2019), pp. 1461-1467. DOI: 10.1109/CEC.2019.8790271 |
EI | |
29. | Djenouri, Y., Djenouri, D., Belhadi, A., Lin, J. C.W., Bendjoudi, A., Fournier-Viger, P. A Novel Parallel Framework for Metaheuristic-based Frequent Itemset Mining. Proc. of 2019 IEEE Congress on Evolutionary Computation (IEEE CEC 2019). pp. 1439-1445 DOI: 10.1109/CEC.2019.8790116 |
EI | |
30. | Lin, J. C.W., ... Fournier-Viger, P., ... (2019). A Project-based PMiner Algorithm in Uncertain Databases. Proc. 2019 Conference on Technologies and Applications of Artificial
Intelligence (TAAI 2019), IEEE, pp. 1-5. DOI: 10.1109/TAAI48200.2019.8959890 |
EI | |
31. | Pham, H. Q., Tran, D., Duong, N. B., Fournier-Viger, P., Ngom, A. (2019). Nuclear: An efficient method for mining frequent itemsets based on kernels and extendable sets. Proc. 6th International Conference on Data Mining and Database, 6(9): 69-86. DOI: 10.5121/csit.2019.90607 |
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32. | Nawaz, M. S., Sun, M., Fournier-Viger, P. (2019). Proof Guidance in PVS with Sequential Pattern Mining. Proc. of 9th Intern. Conf. Fundamentals of Software Engineering (FSEN 2019), 15 pages, Springer, LNCS. DOI: 10.1007/978-3-030-31517-7_4 |
EI | |
2018 | 33. | Fournier-Viger, P., Zhang, Y., Lin, J. C.-W., Fujita, H., Koh, Y.-S. (2018). Mining Local High Utility Itemsets. Proc. 29th International Conference on Database and Expert Systems Applications (DEXA 2018), Springer, pp. 450-460. [source
code] [ppt] DOI: 10.1007/978-3-319-98812-2_41 |
EI CCF-C, corr. auth. |
34. | Lin, J.-C.W., Fournier-Viger, P., Wu, L., Gan, W., Djenouri, Y., Zhang, J. (2018). PPSF: A privacy-preserving data mining library.
Proc. of IEEE International Conference on Data Mining (ICDM 2018) (demo), to appear. [software] DOI: 10.1109/ICDMW.2018.00208 |
EI CCF-B |
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35. | Lin, J. C.-W., Zhang, Y. Y., Fournier-Viger, P., Djenouri, Y., Zhang, J. (2018) A
Metaheuristic Algorithm for Hiding Sensitive Itemsets. Proc. 29th International Conference on Database and Expert Systems Applications (DEXA 2018), Springer, pp. 492-498 DOI: 10.1007/978-3-319-98812-2_45 |
EI CCF-C |
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36. | Fournier-Viger, P., Li, Z., Lin, J. C.-W., Fujita, H., Kiran, U. (2018). Discovering Periodic Patterns Common to Multiple Sequences. Proc. 20th Intern. Conf. on Data Warehousing and Knowledge Discovery (DAWAK 2018), Springer, pp. 231-246 [source
code] [ppt] DOI: 10.1007/978-3-319-98539-8_18 |
EI Acceptance rate: 17%, corr. auth. |
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37. | Lin, J. C.-W., Fournier-Viger, P, Liu, Q., Djenouri, Y., Zhang, J. (2018) Anonymization of Multiple and Personalized Sensitive Attributes. Proc. 20th Intern. Conf. on Data Warehousing and Knowledge Discovery (DAWAK 2018), Springer, pp. 204-215. DOI: 10.1007/978-3-319-98539-8_16 |
EI Acceptance rate: 17% |
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38. | Stirling, M., Koh, Y.S., Fournier-Viger, P., Ravana, S.D. (2018). Concept Drift Detector Selection for Hoeffding Adaptive Trees. Proc. 31st Australasian Joint Conference on Artificial Intelligence (AI 2018), Springer, pp. 730-736. DOI: 10.1007/978-3-030-03991-2_65 |
EI | |
39. | Fournier-Viger, P., Zhang, Y., Lin, J. C.-W., Koh, Y.-S. (2018). Discovering High utility Change Points in Transactional Data. Proc. 13th Intern. Conference on Advanced Data Mining and Applications
(ADMA 2018) Springer LNAI, pp. 392-402 [ppt] DOI: 10.1007/978-3-030-05090-0_33 |
EI, corr. auth. | |
40. | Liu, T., Bai, X., Zhang, D., Cao, X. Fournier-Viger, P., (2018). Influence of Early Season Performance and Team Value on Chinese Football Super League Rankings. Proceedings of 3rd International Conference on Big Data Analysis
(ICBDA 2018), IEEE to appear. DOI: |
EI | |
41. | Fournier-Viger, P., Li, X., Yao, J., Lin, J. C.-W. (2018). Interactive Discovery of Statistically Significant Itemsets. Proc. 31rd Intern. Conf. on Industrial, Engineering and Other
Applications of Applied Intelligent Systems (IEA AIE 2018), Springer LNAI, pp. 101-113. DOI: 10.1007/978-3-319-92058-0_10 |
EI, corr. auth. | |
42. | Wu, J. W.M., Lin, J.C-W., Pirouz, M., Fournier-Viger, P. (2018). New Tighter Upper Bounds for Mining High Average-Utility Itemsets. Proc. 2018 International Conference on Big Data and Education (ICBDE 2018), ACM, pp. 27-32. DOI: 10.1145/3206157.3206168 |
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43. | Amirat, H., Benslimane, A., Fournier-Viger, P., Lagraa, N. (2018). LocRec: Rule-based Successive Location Recommendation in LBSN. Proceedings of 2018 IEEE International Conference on Communications (ICC 2018), IEEE, pp. 1-6. DOI: 10.1109/ICC.2018.8422183 |
EI CCF-C |
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44. | Djenouri, Y., Lin, J. C.-W., Djenouri, D., Belhadi, A., Fournier-Viger, P. (2018). GBSO-RSS: GPU-based BSO for Rules Space Summarization. Proc. 1st International Conference on Big Data and Deep Learning Applications (ICBDL 2018), 123-129. DOI: 10.1007/978-981-13-0869-7_14 |
EI ISBN: 978-981-13-0869-7 |
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45. | de Souza, K. V.-C. K., Almhana, C., Fournier-Viger, P., Almhana, J. (2018). Radio Data Transmission Reduction in Power-Constrained WSN. Proceedings of 14th International Wireless Communications & Mobile Computing Conference (IWCMC 2018), IEEE, pp. 285-290. DOI: 10.1109/IWCMC.2018.8450353 |
EI | |
46. | Lin, J. C.-W., Li, Y., Fournier-Viger, P., Tan, L. (2018). Mining high utility itemsets from multiple databases. Proc. 2nd Intern. Conf. on Smart Vehicular Technology, Transportation, Communication and Applications (VTCA 2018), Springer, pp. 139-146. DOI: 10.1007/978-3-030-04585-2_17 |
EI ISBN: 978-3-030-04585-2 |
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2017 | 47. | Kiran, U., Venkatesh, J. N., Fournier-Viger, P., Toyoda, M., Reddy, P. K., Kitsuregawa, M. (2017). Discovering Periodic Patterns in Non-Uniform Temporal Databases. Proc. 21st Pacific-Asia Conf. Knowledge Discovery and
Data Mining (PAKDD 2017) Part II, Springer, LNAI, pp. 604-617. DOI: 10.1007/978-3-319-57529-2_47 |
EI Acceptance rate: 28% |
48. | Gan, W., Lin, J. C.-W., Fournier-Viger, P., Chao, H.-C., Tseng, V.S. (2017). Mining High-Utility Itemsets with both Positive and Negative Unit Profits from Uncertain Databases. Proc. 21st Pacific-Asia Conf. Knowledge Discovery and Data Mining (PAKDD 2017) Part I, Springer, LNAI, pp. 434-446 DOI: 10.1007/978-3-319-57454-7_34 |
EI Acceptance rate: 28% |
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49. | Lin, J. C.-W., Zhang, J., Fournier-Viger, P. (2017). High Utility Sequential Pattern Mining with Multiple Minimum Utility Thresholds. Proc. of the APWeb-WAIM Joint Conference on Web and Big Data 2017(APWeb-WAIM 2017), Springer, pp.215-229. DOI: 10.1007/978-3-319-63579-8_17 |
EI Acceptance rate: 18% CCF-C |
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50. | Gan, W., Lin, J. C.-W., Fournier-Viger, P., Chao, H.-C.(2017). Exploiting High Utility Occupancy Patterns. Proc. of the APWeb-WAIM Joint Conference on Web and Big Data 2017(APWeb-WAIM 2017), Springer, pp.239-247 DOI: 10.1007/978-3-319-63579-8_19 |
EI Acceptance rate: 18% CCF-C |
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51. | Gan, W., Lin, J. C.-W., Fournier-Viger, P., Chao, H.-C.(2017). Extracting Non-redundant Correlated High Utility Purchase Behaviors. Proc. 19th Intern. Conf. on Data Warehousing and Knowledge Discovery (DaWaK 2017), Springer, pp. 433-446 DOI: 10.1007/978-3-319-64283-3_32 |
EI | |
52. | Djenouri, Y., Belhadi, A., Fournier-Viger, P., Lin, J. C.-W. (2017). An Hybrid Multi-Core/GPU-based Mimetic Algorithm for Big Association Rule Mining. Proc. 11th Intern. Conference on Genetic and
Evolutionary Computing (ICGEC 2017), Springer, pp. 56-65 DOI: 10.1007/978-981-10-6487-6_8 |
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53. | Zhang, X., Wu, C.-W., Fournier-Viger, P., Van, L.-D., Tseng, Y.-C. (2017).
Analyzing Students' Attention in Class Using Wearable Devices. Proc. 18th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM 2017), IEEE, pp. 1-9. DOI: 10.1109/WoWMoM.2017.7974306 |
EI CCF-C |
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54. | Dalmas, B., Fournier-Viger, P., Norre, S. (2017). TWINCLE: A Constrained Sequential Rule Mining Algorithm for Event Logs. Proc.
9th International KES Conference (IDT-KES 2017), Elsevier, pp. 205-214 |
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55. | Lin, J. C.-W., Ren, S., Fournier-Viger, P., Hong, T.-P. (2017). Mining of High Average-Utility Itemsets with a Tighter Upper-Bound Model. Proceedings of 4th Multidisciplinary International Social Networks Conference on Social Informatics 2017 (MISNC 2017), to appear. DOI: |
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56. | Liu, T., Fournier-Viger, P., Hohmann, A. (2017). Using Diagnostic Analysis to Discover Offensive Patterns in a Football Game. Proceedings of International Conference on Data Science and Business Analytics (ICDSBA 2017), Springer, pp. 381-386. |
ISBN: 978-3-319-72745-5 | |
57. | de Souza, K. V.-C. K., Almhana, C., Fournier-Viger, P., Almhana, J. (2017). Energy-Efficient Partitioning Clustering Algorithm for Wireless Sensor Network. Proceedings of 10th EAI International Wireless Internet Conference (WiCON 2017), Springer, pp. 14-23. DOI: 10.1007/978-3-319-90802-1_2 |
EI | |
2016 | 58. | Fournier-Viger, P., Lin, C.W., Wu, C.-W., Tseng, V. S., Faghihi, U. (2016). Mining Minimal High-Utility Itemsets. Proc. 27th International Conference on Database and Expert Systems Applications (DEXA 2016). Springer, LNCS, pp. 88-101. [ppt] [source
code] [video] DOI: 10.1007/978-3-319-44403-1_6 |
EI CCF-C, corr. auth. |
59. | Lin, C.W., Gan, W., Fournier-Viger, P., Chen, H.-C. (2016). More Efficient Algorithms for Mining High-Utility Itemsets with Multiple Minimum Thresholds. Proc. 27th International Conference on Database and Expert Systems Applications (DEXA 2016). Springer, LNCS, pp. 71-87. DOI: 10.1007/978-3-319-44403-1_5 |
EI CCF-C |
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60. | Lin, C.W., Gan, W., Fournier-Viger, P., Chen, H.-C. (2016). Mining Recent High-Utility Patterns from Temporal Databases with Time-Sensitive Constraint. Proc. 18th Intern. Conf. on Data Warehousing and Knowledge Discovery (DAWAK 2016). Springer, LNCS, pp. 3-16 DOI: 10.1007/978-3-319-43946-4_1 |
EI |
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61. | Fournier-Viger, P., Lin, C.W., Gomariz, A., Soltani, A., Deng, Z., Lam, H. T. (2016). The SPMF Open-Source Data Mining Library Version 2. Proc. 19th European Conference on Principles of Data Mining and Knowledge Discovery (PKDD 2016) Part III. Springer, pp. 36-40. [software] DOI: 10.1007/978-3-319-46131-1_8 |
EI CCF-B, corr. auth. |
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62. | Fournier-Viger, P., Zida, S. Lin, C.W., Wu, C.-W., Tseng, V. S. (2016). EFIM-Closed: Fast and Memory Efficient Discovery of Closed High-Utility Itemsets. Proc. 12th Intern. Conference on Machine Learning and Data Mining (MLDM 2016). Springer, LNAI, pp. 199-213. [ppt] [source
code] DOI: 10.1007/978-3-319-41920-6_15 |
EI, corr. auth. |
|
63. | Lin, C.W., Gan, W., Fournier-Viger, P., Hong, T.-P. (2016). Efficient Mining of Weighted Frequent Itemsets in Uncertain Databases. Proc. 12th Intern. Conference on Machine Learning and Data Mining (MLDM 2016). Springer, LNAI, pp. 236-250. DOI: 10.1007/978-3-319-41920-6_18 |
EI |
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64. | Fournier-Viger, P., Lin, C.W., Duong, Q.-H., Dam, T.-L. (2016). FHM+: Faster High-Utility Itemset Mining using Length Upper-Bound Reduction. Proc. 29th Intern. Conf. on Industrial, Engineering and Other
Applications of Applied Intelligent Systems (IEA AIE 2016), Springer LNAI, pp. 115-127. [ppt] [source
code] DOI: 10.1007/978-3-319-42007-3_11 |
EI, corr. auth. |
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65. | Lin, C.W., Li, T., Fournier-Viger, P., Hong, T.-P., Su, J.-W. (2016). Fast Algorithms for Mining Multiple Fuzzy Frequent Itemsets. Proc. 16th IEEE Conference on Fuzzy Systems (FUZZY-IEEE 2016), IEEE, to appear DOI: 10.3233/IFS-151936 |
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66. | Lin, C.W., Ren, S., Fournier-Viger, P., Su, J.-H., Vo, B. (2016). A More Efficient Algorithm to Mine High Average-Utility Itemsets. Proc. 12th Intern. Conf. on
Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2016). Springer, pp 101-110. DOI: |
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67. | Lin, C.-W., Zhang, J., Fournier-Viger, P., Hong, T.-P., Chen, C.-M. (2016). Efficient Mining of Short Periodic High-Utility Itemsets. Proc. 27th IEEE International Conference on Systems, Man, and Cybernetics (SMC 2016). IEEE, to appear DOI: 10.1109/SMC.2016.7844710 |
CCF-C |
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68. | Lin, C.W., Gan, W., Fournier-Viger, P., Han-Chieh, C. (2016). More Efficient Algorithms for Mining Frequent Patterns with Multiple Minimum Supports. Proc.
17th International Conference Web-Age Information Management (WAIM 2016), Springer LNAI, pp. 3-16. DOI: 10.1007/978-3-319-39937-9_1 |
CCF-C |
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69. | Lin, C.W., Gan, W., Fournier-Viger, P., Han-Chieh, C. (2016). Mining Recent High Expected Weighted Itemset from Uncertain Databases. Proc. 18th Asia-Pacific Web Conference (APWeb
2016), Springer, LNCS, pp. 581-593. DOI: 10.1007/978-3-319-45814-4_47 |
CCF-C |
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70. | Lin, C.W., Li, T., Fournier-Viger, P., Hong, T. P., Tseng, V. S. (2016). Efficient Mining of Uncertain Data to Discover High-Utility Itemsets. Proc.
17th International Conference Web-Age Information Management (WAIM 2016), Springer LNAI, pp. 17-30. DOI: 10.1007/978-3-319-39937-9_2 |
CCF-C |
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71. | Voznak, M., Rozhon, J., Mikulec, M., Rezac, F., Komosny, D., Lin, J.C.-W.,Fournier-Viger, P. (2016) Employing the neural networks to parametrically assess the quality of a voice call.
Proc. 2016 International Symposium on Performance Evaluation of Computer and Telecommunication Systems (SPECTS 2016), pp. 1-5. DOI: 10.1109/SPECTS.2016.7570521 |
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72. | Fournier-Viger, P., Lin, C. W., Dinh, T., Le, H. B. (2016). Mining Correlated High-Utility Itemsets Using the Bond Measure. Proc. 11 th International Conference on Hybrid Artificial Intelligence Systems (HAIS 2016), Springer LNAI, pp.53-65. [ppt] [source code] DOI: 10.1007/978-3-319-32034-2_5 |
corr. auth. |
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73. | Fournier-Viger, P., Lin, C.W., Duong, Q.-H., Dam, T.-L. (2016). PHM: Mining Periodic High-Utility Itemsets. Proc. 16th Industrial Conference on Data Mining. Springer LNAI 9728, pp. 64-79. [ppt] [source
code] DOI: 10.1007/978-3-319-41561-1_6 |
* Nominated for best paper award (one of the three finalists)* corr. auth. |
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74. | Lin, C.W., Li, T., Fournier-Viger, P., Hong, T.-P., Su, J.-H. (2016). Efficient Mining of High Average-Utility Itemsets with Multiple Minimum Thresholds. Proc. 16th Industrial Conference on Data Mining. Springer LNAI 9728, pp. 14-28. DOI: 10.1007/978-3-319-41561-1_2 |
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75. | Fournier-Viger, P., Zida, S., Lin, C.W., Wu, C.W., Tseng., V.
(2016). Efficient closed high-utility itemset-mining. Proc. 31th Symposium on Applied Computing (ACM SAC 2016). ACM Press, pp. 898-900. [source code] DOI: 10.1145/2851613.2851884 |
* Nominated for best poster award (one of the six finalists)* |
|
76. | Lin, C.W., Gan, W., Fournier-Viger, P., Hong, T.-P. (2016). Efficient Algorithms for Mining Recent Weighted Frequent Itemsets in
Temporal Transactional Databases. Proc. 31th Symposium on
Applied Computing (ACM SAC 2016). ACM Press, pp.861-866 DOI: 10.1145/2851613.2851648 |
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77. | Faghihi, U., Chatman, D., Gautier, N., Gholson, J., Gholson, J., Lipkal, M., Dill, R, Fournier-Viger, P., Maldonado-Bouchard, S. (2016). How to Apply Gamification Techniques to Design a Gaming nvironment for Algebra concepts. Proc. 3rd Intern. Conf. on E-Learning, E-Education, and Online Training (eLEOT 2016), Springer LNICST, 8 pages. DOI: 10.1007/978-3-319-49625-2_8 |
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78. | Pokou J. M., Fournier-Viger, P., Moghrabi, C. (2016). Authorship Attribution Using Small Sets of Frequent Part-of-Speech Skip-grams. Proc. 29th Intern. Florida Artificial Intelligence Research Society Conference (FLAIRS 29), AAAI Press, pp. 86-91 [datasets]. DOI: |
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79. | Pokou J. M., Fournier-Viger, P., Moghrabi, C. (2016). Using Frequent Fixed or Variable-Length POS Ngrams or Skip-grams for Blog Authorship Attribution . Proc. 12th Intern. Conf. on Artificial Intelligence Applications and Innovations (AIAI 2016), Springer LNAI, pp. 63-74 [datasets]. DOI: 10.1007/978-3-319-44944-9_6 |
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80. | Lin, J. C.-W., Liu, Q., Fournier-Viger, P., Hong, T.-P., Zhan, J., Voznak, M. (2016). An Efficient Anonymous System for Transaction Data. Proceedings of 3rd Multidisciplinary International Social Networks Conference on Social Informatics 2016 (MISNC 2016), pp. 28. |
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81. | Lin, J. C.-W., Gan, W., Fournier-Viger, P., Hong, T.-P.
(2016). Mining Discriminative High Utility Patterns.
Proc. 8th Asian Conference on Intelligent Information and Database
Systems (ACIIDS 2016), Springer, pp. 219-229. DOI: 10.1007/978-3-662-49390-8_21 |
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82. | Lin, J. C.-W., Lv, X., Fournier-Viger, P., Wu, T.-Y., Hong, T.-P. (2016). Efficient Mining of Fuzzy Frequent Itemsets with Type-2 Membership Functions. Proc. 8th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2016), Springer, pp. 191-200. DOI: 10.1007/978-3-662-49390-8_18 |
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83. | Fournier-Viger, P., Lin, C.-W., Duong, Q.-H., Dam, T.-L., Sevcic, L., Uhrin, D., Voznak, M. (2016). PFPM: Discovering Periodic Frequent Patterns with Novel Periodicity Measures.
Proc. 2nd Czech-China Scientific Conference 2016, Elsevier, 10 pages. [source
code] [video] [ppt] DOI: |
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84. | Pokou J. M., Fournier-Viger, P., Moghrabi, C. (2016). Authorship Attribution using Variable-Length Part-of-Speech Patterns. Proc. 7th
Intern. Conf. on Agents and Artificial Intelligence (ICAART 2016), pp. 354-361 [datasets]. DOI: 10.5220/0005710103540361 |
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2015 | 85. | Zida, S., Fournier-Viger, P., Lin, J. C.-W., Wu, C.-W., Tseng, V.S. (2015). EFIM: A Highly Efficient Algorithm for High-Utility Itemset Mining. Proceedings of the 14th Mexican Intern. Conference on Artificial Intelligence (MICAI 2015), Springer LNAI 9413, pp. 530-546. [ppt] [source code] | |
86. | Dougnon, Y. R., Fournier-Viger, P., Lin, J. C.-W., Nkambou, R. (2015). More Accurate User Profile Inference in Online Social Networks. Proceedings of the 14th Mexican Intern. Conference on Artificial Intelligence (MICAI 2015), Springer LNAI 9414, pp. 533-546. | ||
87. | Fournier-Viger, P., Lin, J. C.-W., Gueniche, T., Barhate, P. (2015). Efficient Incremental High Utility Itemset Mining. Proc. 5th ASE International Conference on Big Data (BigData 2015), 6 pages. [ppt] [video] [source code] | ||
88. | Lin, J. C.-W., Gan, W., Fournier-Viger, P., Hong, T.-P., Tseng, V. S. (2015). Mining Potential High-Utility Itemsets over Uncertain Databases. Proc. 5th ASE International Conference on Big Data (BigData 2015), 6 pages. [video] | ||
89. | Gueniche, T., Fournier-Viger, P., Raman, R., Tseng, V. S.
(2015). CPT+:
Decreasing the time/space complexity of the Compact Prediction Tree. Proc. 19th Pacific-Asia Conf. Knowledge Discovery and
Data Mining (PAKDD 2015), Springer, LNAI9078, pp. 625-636. [ppt] [Source code: Java version (original) and a Cython version (unofficial)] |
accept. rate: 6 % CCF-C |
|
90. | Zida, S., Fournier-Viger, P., Wu, C.-W., Lin, J. C. W., Tseng, V.S., (2015). Efficient Mining of High Utility Sequential Rules. Proc. 11th Intern. Conference on Machine Learning and Data Mining (MLDM 2015). Springer, LNAI 9166, pp. 157-171. [source code] | * Nominated for best paper award (one of the three finalists)* | |
91. | Wu, C.W., Fournier-Viger, P., Gu, J.-Y., Tseng, V.S. (2015). Mining Closed+ High Utility Itemsets without Candidate Generation. Proc. 2015 Conference on Technologies and Applications of Artificial Intelligence (TAAI 2015), pp. 187-194. [source code] | * Merit Paper Award * | |
92. | Tseng, V. S., Wu, C.-W., Lin, J.-H., Fournier-Viger, P. (2015). UP-Miner: A Utility Pattern Mining Toolbox. Proc. of IEEE International Conference on Data Mining (ICDM 2015) (demo), pp. 1656-1659. | CCF-B |
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93. | Lin, J. C.-W., Gan, W., Fournier-Viger, P., Hong, T.-P., Tseng. V. (2015). Mining High-Utility Itemsets with Various Discount Strategies. Proc. 2015 IEEE/ACM International Conference on Data Science and Advanced Analytics (DSAA’2015), 6 pages, pp. 1-10. | accept. rate: 22 % CCF-C |
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94. | Lin, J. C.-W., Gan, W., Fournier-Viger, P., Hong, T.-P. (2015). Mining Weighted-Frequent Itemsets with Time-Sensitive Constraint. Proc. 17th Asia-Pacific Web Conference (APWeb 2015), Springer, LNCS, pp.635-646. | accept. rate: 23 % CCF-C |
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95. | Dougnon, Y. R., Fournier-Viger, P., Lin, J. C.-W., Nkambou, R. (2015). Accurate Social Network User Profiling. Proc. 38th German Conference on Artificial Intelligence (KI 2015), Springer LNAI 9324, pp. 265-270. | ||
96. | Lin, J. C.-W., Yang, L., Fournier-Viger, P., Wu, M.-T., Hong, T.-P., Wang, L. (2015). A Swarm-based Approach to Mine High-Utility Itemsets. Proc. 2nd Multidisciplinary Intern. Social Networks Conference (MISNC 2015). Springer, pp. 572-581. | ||
97 |
Lin, J. C.-W., Wu, T.-S., Fournier-Viger, P., Lin, G., Hong, T.-P. (2015). A Sanitization Approach of Privacy Preserving Utility Mining, Proc. 9th Intern. Conference on Genetic and Evolutionary Computing (ICGEC 2015), pp. 47-57. | *Best Paper Award* | |
98 |
Lin, J. C-W., Liu, Q., Fournier-Viger, P., Hong, T.-P., Pan, J. S. (2015). A Swarm-based Sanitization Approach for Hiding Confidential Itemsets. Proc. of the Eleventh Intern. Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 572-583. | ||
99. | Lin, J. C.-W., Gan, W., Fournier-Viger, P., Hong, T.-P. (2015). Mining High-Utility Itemsets with Multiple Minimum Utility Thresholds. Proc. 8th Intern. C* Conference on Computer Science & Software Engineering (C3S2E15). ACM, pp. 9-17. | ||
100. | Dougnon, Y. R., Fournier-Viger, P., Nkambou, R. (2015). Inferring User Profiles in Social Networks using a Partial Social Graph. Proc. 28th Canadian Conference on Artificial Intelligence (AI 2015), Springer, LNAI 9091, pp. 84-99. | accept. rate: 18 % | |
101. | Gueniche, T., Fournier-Viger, P. (2015). Réduction de la complexité spatiale et temporelle du Compact Prediction Tree pour la prédiction de séquences. Proc. 15ème conférence Interne sur l'extraction et la gestion des connaissances (EGC 2015), Revue des Nouvelles Technologies de l'Information, vol. E-28, pp.59-70. | * Nominated for best paper award * | |
102. | Fournier-Viger, P., Zida, S. (2015). FOSHU: Faster On-Shelf High Utility Itemset Mining– with or without negative unit profit. Proc. 30th Symposium on Applied Computing (ACM SAC 2015). ACM Press, pp. 857-864. [source code] | accept. rate: 20 % | |
2014 | 103. | Fournier-Viger, P., Wu, C.W., Tseng, V.S. (2014). Novel Concise Representations of High Utility Itemsets using Generator Patterns. Proc. 10th Intern. Conference on Advanced Data Mining and Applications (ADMA 2014), Springer LNCS 8933, pp. 30-43. [ppt] [source code] | *Best Paper Award* |
104. | Fournier-Viger, P. (2014). FHN: Efficient Mining of High-Utility Itemsets with Negative Unit Profits. Proc. 10th Intern. Conference on Advanced Data Mining and Applications (ADMA 2014), Springer LNCS 8933, pp. 16-29. [ppt][source code] | ||
105. | Fournier-Viger, P., Gomariz, A., Campos, M., Thomas, R. (2014). Fast Vertical Mining of Sequential Patterns Using Co-occurrence Information. Proc. 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2014) Part 1, Springer, LNAI, 8443. pp. 40-52. [ppt][source code] | accept. rate: 27 % CCF-C |
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106. | Fournier-Viger, P., Gomariz, A., Sebek, M., Hlosta, M. (2014). VGEN: Fast Vertical Mining of Sequential Generator Patterns. Proc. 16th Intern. Conf. on Data Warehousing and Knowledge Discovery (DAWAK 2014), Springer, LNCS 8646, pp. 476--488. [source code] | accept. rate: 31 % | |
107. | Fournier-Viger, P., Gueniche, T., Zida, S., Tseng, V. S. (2014). ERMiner: Sequential Rule Mining using Equivalence Classes. Proc. 13th Intern. Symposium on Intelligent Data Analysis (IDA 2014), Springer, LNCS 8819, pp. 108-119. [source code] | ||
108. | Mwamikazi, E., Fournier-Viger, P., Moghrabi, C., Baudouin, R. (2014). A Dynamic Questionnaire to Further Reduce Questions in Learning Style Assessment. Proc. 10th Int. Conf. Artificial Intelligence Applications and Innovations (AIAI2014), Springer, LNAI, pp. 224-235. | ||
109. | Fournier-Viger, P., Wu, C.-W., Zida, S., Tseng, V. S. (2014) FHM: Faster High-Utility Itemset Mining using Estimated Utility Co-occurrence Pruning. Proc. 21st Intern. Symposium on Methodologies for Intelligent Systems (ISMIS 2014), Springer, LNAI, pp. 83-92. [ppt][source code] | ||
110. | Gueniche, T., Fournier-Viger, P., Nkambou, R., Tseng, V. S. (2014) WBPL: An Open-Source Library for Predicting Web Surfing Behaviors. Proc. 21st Intern. Symposium on Methodologies for Intelligent Systems (ISMIS 2014), Springer, LNAI, pp. 524-529. | ||
111. | Fournier-Viger, P., Wu, C.-W., Gomariz, A., Tseng, V. S. (2014). VMSP: Efficient Vertical Mining of Maximal Sequential Patterns. Proc. 27th Canadian Conference on Artificial Intelligence (AI 2014), Springer, LNAI, pp. 83-94. [ppt] [source code] | accept. rate: 23 % | |
112. | Mwamikazi, E., Fournier-Viger, P., Moghrabi, C., Barhoumi, A., Baudouin, R. (2014). An Adaptive Questionnaire for Automatic Identification of Learning Styles. Proc. 27th Intern. Conf. on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA AIE 2014), Springer, LNAI 8481, pp. 399-409. | ||
2013 | 113. | Fournier-Viger, P., Gomariz, A., Gueniche, T., Mwamikazi, E., Thomas, R. (2013). TKS: Efficient Mining of Top-K Sequential Patterns. Proc. 9th Intern. Conference on Advanced Data Mining and Applications (ADMA 2013) Part I, Springer LNAI 8346, pp. 109-120. [ppt] [source code] | accept. rate: 14 % ( full paper) |
114. | Gueniche, T., Fournier-Viger, P., Tseng, V. S. (2013). Compact Prediction Tree:
A Lossless Model for Accurate Sequence Prediction. Proc.
9th Intern. Conference on Advanced Data Mining and Applications (ADMA
2013) Part II, Springer LNAI 8347, pp. 177-188. [ppt] [Source code: Java version (original) and a Cython version (unofficial)] |
accept. rate: 14 % (full paper) |
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115. | Fournier-Viger, P., Wu, C.-W., Tseng, V. S. (2013). Mining Maximal Sequential Patterns without Candidate Maintenance. Proc. 9th Intern. Conference on Advanced Data Mining and Applications (ADMA 2013) Part I, Springer LNAI 8346, pp. 169-180. [ppt] [source code] | ||
116. | Fournier-Viger, P., Mwamikazi, E., Gueniche, T., Faghihi, U. (2013). Memory Efficient Itemset Tree for Targeted Association Rule Mining. Proc. 9th Intern. Conference on Advanced Data Mining and Applications (ADMA 2013) Part II, Springer LNAI 8347, pp. 95-106. [ppt] [source code] | ||
117. | Fournier-Viger, P., Tseng, V. S. (2013). TNS: Mining Top-K Non-Redundant Sequential Rules. Proc. 28th Symposium on Applied Computing (ACM SAC 2013). ACM Press, pp. 164-166. [source code] | ||
118. | Snow, E., Moghrabi, C., Fournier-Viger, P. (2013). Assessing Procedural Knowledge in Free-text Answers through a Hybrid Semantic Web Approach. Proc. of the 25th IEEE Intern. Conference on Tools with Artificial Intelligence (ICTAI 2013), IEEE, pp. 698-706. | CCF-C |
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2012 | 119. | Fournier-Viger, P. Gueniche, T., Tseng, V.S. (2012). Using Partially-Ordered Sequential Rules to Generate More Accurate Sequence Prediction. Proc. 8th Intern. Conference on Advanced Data Mining and Applications (ADMA 2012), Springer LNAI 7713, pp. 431-442. | accept. rate: 19% |
120. | Fournier-Viger, P., Nkambou, R., Mayers, A., Mephu Nguifo, E., Faghihi, U. (2012). Multi-Paradigm Generation of Tutoring Feedback in Robotic Arm Manipulation Training. Proceedings of the 11th Intern. Conf. on Intelligent Tutoring Systems (ITS 2012), LNCS 7315, Springer, pp. 233-242. | accept. rate: 15 % | |
121. | Fournier-Viger, P., Tseng, V.S. (2012). Mining Top-K Non-Redundant Association Rules. Proc. 20th Intern. Symposium on Methodologies for Intelligent Systems (ISMIS 2012), Springer, LNCS 7661, pp. 31- 40. [source code] | * Nominated for best paper award * | |
122. | Fournier-Viger, P., Wu, C.-W., Tseng, V. S. (2012). Mining Top-K Association Rules. Proceedings of the 25th Canadian Conf. on Artificial Intelligence (AI 2012), Springer, LNAI 7310, pp. 61-73. [source code] [ppt] | accept. rate: 29 % | |
123. | Fournier-Viger, P., Wu, C.-W., Tseng, V.S., Nkambou, R. (2012). Mining Sequential Rules Common to Several Sequences with the Window Size Constraint. Proceedings of the 25th Canadian Conf. on Artificial Intelligence (AI 2012), Springer, LNAI 7310, pp.299-304. [source code] | ||
2011 | 124. | Wu, C.-W., Fournier-Viger, P., Yu., P. S., Tseng, V. S. (2011). Efficient Mining of a Concise and Lossless Representation of High Utility Itemsets. Proceedings of the 11th IEEE Intern. Conference on Data Mining (ICDM 2011). IEEE CS Press, pp.824-833. | accept. rate: 12 % CCF-B |
125. | Fournier-Viger, P., Tseng, V. S. (2011). Mining Top-K Sequential Rules. Proceedings of the 7th Intern. Conf. on Advanced Data Mining and Applications (ADMA 2011). LNAI 7121, Springer, pp.180-194. [source code] [ppt] | accept. rate: 18 % ( full paper) |
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126. | Fournier-Viger, P., Nkambou, R., Tseng, V. S. (2011). RuleGrowth: Mining Sequential Rules Common to Several Sequences by Pattern-Growth. Proceedings of the 26th Symposium on Applied Computing (ACM SAC 2011). ACM Press, pp. 954-959. [source code][ppt] | ||
127. | Fournier-Viger, P., Nkambou, R., Mayers, A., Mephu Nguifo, E., Faghihi, U. (2011). An Hybrid Expertise Model to Support Tutoring Services in Robotic Arm Manipulations. Proceedings of the 10th Mexican Intern. Conference on Artificial Intelligence (MICAI 2011), LNAI 7094, Springer, pp. 478-489. | ||
128. | Faghihi, U., Fournier-Viger, P., Nkambou, R. (2011).A Cognitive Tutoring Agent with Episodic and Causal Learning Capabilities.Proceedings of the 15th Intern. Conf. on Artificial Intelligence and Education (AIED 2011). IOS Press, pp. 72-80. | accept. rate: 32% | |
129. | Faghihi, U., Fournier-Viger, P., Nkambou, R. (2011). Implementing an Efficient Causal Learning Mechanism in a Cognitive Tutoring Agent. Proceedings of the 24th Intern.Conf. on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA-AIE 2011), LNAI 6704, Springer, pp.27-36. | ||
130. | Faghihi, U., Fournier-Viger, P., Nkambou, R. (2011). A Cognitive Tutoring Agent with Automatic Reasoning Capabilities.Proceedings of the 24th Intern. Florida Artificial Intelligence Research Society Conference (FLAIRS 2011), AAAI press, pp.448-449. | ||
<2010 | 131. | Fournier-Viger, P., Faghihi, U., Nkambou, R., Mephu Nguifo, E. (2010). CMRules: An Efficient Algorithm for Mining Sequential Rules Common to Several Sequences. Proceedings of the 23th Intern. Florida Artificial Intelligence Research Society Conference (FLAIRS 2010). AAAI press, pp. 410-415. [source code] [ppt] | |
132. | Faghihi, U., Fournier-Viger, P., Nkambou, R. & Poirier, P. (2010). The Combination of a Causal Learning and an Emotional Learning Mechanism for an Improved Cognitive Tutoring Agent. Proceedings of the 23th Intern.Conf. on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA-AIE 2010), LNAI 6097, Springer, pp. 438-449. | ||
133. | Fournier-Viger, P., Nkambou, R., Mephu Nguifo, E. & Mayers, A.(2010). ITS in Ill-defined Domains: Toward Hybrid Approaches. Proceedings of the 10th Intern. Conf. on Intelligent Tutoring Systems (ITS 2010), LNCS 6095, Springer, pp. 749-751. | ||
134. | Fournier-Viger, P., Nkambou, R., Mephu Nguifo, E. (2009). Exploiting Partial Problem Spaces Learned from Users' Interactions to Provide Key Tutoring Services in Procedural and Ill-Defined Domains. Proc. 14th Intern. Conf. on Artificial Intelligence and Education (AIED 2009). IOS Press. pp. 383-390. | ||
135. | Faghihi, U., Fournier-Viger, P., Nkambou, R. & Poirier, P. (2009). A Generic Episodic Learning Model Implemented in a Cognitive Agent by Means of Temporal Pattern Mining. Proc. 22nd Intern. Conf. on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA-AIE 2009), LNAI 5579, Springer, pp. 545-555. | ||
136. | Fournier-Viger, P., Nkambou, R., Mephu Nguifo, E. & Faghihi, U. (2009). Building Agents that Learn by Observing other Agents Performing a Task - A Sequential Pattern Mining Approach. Proceedings of the 22nd Intern.Conf. on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA-AIE 2009), SCI 214, Springer, pp. 279-284. | ||
137. | Faghihi, U., Fournier-Viger, P., Nkambou, R., Poirier, P., Mayers, A. (2009). How Emotional Mechanism Helps Episodic Learning in a Cognitive Agent. Proceedings of the 2009 IEEE Symposium on Intelligent Agents, pp. 23-30. | ||
138. | Faghihi, U., Nkambou, R, Poirier, P., & Fournier-Viger, P. (2009). Emotional Learning and a Combined Centralist-Peripheralist Based Architecture for a More Efficient Cognitive Agent. Proceedings of the 7th IEEE Intern. Conference on Industrial Technology (ICIT 2009), 6 pages. | ||
139. | Fournier-Viger, P., Nkambou, R & Mephu Nguifo, E. (2008), A Knowledge Discovery Framework for Learning Task Models from User Interactions in Intelligent Tutoring Systems. Proceedings of the 7th Mexican Intern. Conference on Artificial Intelligence (MICAI 2008). LNAI 5317, Springer, pp. 765-778. | *Best Paper Award* accept. rate: 25% |
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140. | Fournier-Viger, P., Nkambou, R., Mayers, A. (2008). A Framework for Evaluating Semantic Knowledge in Problem-Solving-Based Intelligent Tutoring Systems. Proceedings of the 21th Intern. Florida Artificial Intelligence Research Society Conference (FLAIRS 2008). AAAI press, pp. 409-414. | ||
141. | Nkambou, R, Mephu Nguifo, E. & Fournier-Viger, P. (2008). Using Knowledge Discovery Techniques to Support Tutoring in an Ill-Defined Domain. Proceedings of the 9th Intern. Conference on Intelligent Tutoring Systems (ITS 2008). LNCS 5091, Springer, pp. 395-405. | * Nominated for
best paper award * accept. rate: 30% |
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142. | Fournier-Viger, P., Nkambou, R., Mayers, A. (2008). Evaluating Spatial Knowledge through Problem-Solving in Virtual Learning Environments. Proceedings of the Third European Conference on Technology Enhanced Learning (EC-TEL 2008). LNCS 5192, Springer, pp 15-26. | *In top 14* accept. rate: 21% |
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143. | Fournier-Viger, P., Nkambou, R & Mephu Nguifo, E. (2008). A Data Mining Framework for the Acquisition of Procedural Knowledge in Intelligent Tutoring Systems. Proceedings of the 16th Intern. Conference on Computers in Education (ICCE 2008). pp. 153-157. | ||
144. | Nkambou, R., Mephu Nguifo, E., Couturier, O. & Fournier-Viger, P. (2007). Problem-Solving Knowledge Mining from Users' Actions in an Intelligent Tutoring System. Proceedings of the 19th Canadian Conference on Artificial Intelligence (AI'2007), LNAI 3501, Springer, pp: 393-404. | accept. rate: 17% | |
145. | Fournier-Viger, P., Nkambou, R., Mayers, A., Dubois, D. (2007). Automatic Evaluation of Spatial Representations for Complex Robotic Arms Manipulations. Proceedings of the 7th IEEE Intern. Conference on Advanced Learning Technologies (ICALT 2007), pp: 279-281. | ||
146. | Nkambou R., Mephu Nguifo, E., Couturier, O., Fournier-Viger, P. (2007). A Framework for Problem-Solving Knowledge Mining from Users’ Actions. Proceedings of the 13th Intern. Conference on Artificial Intelligence in Education (AIED 2007). pp: 623-625. | ||
147. | Najjar, M., Fournier-Viger, P., Lebeau, J.-F. & Mayers., A. (2006). Recalling Recollections according to Temporal Contexts - Applying a Novel Cognitive Knowledge Representation Approach. Proceedings of the 5th IEEE Intern. Conference on Cognitive Informatics (ICCI 2006), pp. 424-433. | ||
148. | Fournier-Viger P., Najjar, M., Mayers, A., Nkambou, R. (2006). From Black-box Learning Objects to Glass-Box Learning Objects. Proceedings of the 8th Intern. Conference on Intelligent Tutoring Systems (ITS 2006). LNCS 4053, Springer, pp: 258-267. | accept. rate: 32% | |
149. | Najjar, M., Fournier-Viger, P., Mayers, A., Bouchard, F. (2005). Memorising Remembrances in Computational Modelling of Interrupted Activities. Proceedings of the 7th Intern. Conference on Computational Intelligence & Natural Computing (CINC 2005). pp: 483-486. | ||
150. | Najjar, M., Fournier-Viger, P., Mayers, A., Hallé, J. (2005). DOKGETT - An Authoring Tool for Cognitive Model-based Generation of the Knowledge. Proceedings of the 5th IEEE Intern. Conference on Advanced Learning Technologies (ICALT 2005), pp: 371-375. | ||
151. | Najjar, M., Fournier-Viger, P., Mayers, A., Hallé, J. (2005). Tools and Structures for Modelling Domain/User Knowledge in Virtual Learning. Proceedings of the 16th AACE World Conference on Educational Multimedia, Hypermedia & Telecommunications (ED-MEDIA 2005). pp: 4023-4028. | ||
152. | Fournier-Viger, P., Najjar, M., Mayers, A. (2005). Combining the Learning Objects Paradigm with Cognitive Modelling Theories - a Novel Approach for Knowledge Engineering. Proceedings of the ITI 3rd Intern. Conference on Information & Communication Technology (ICICT 2005). pp: 565-578. | ||
153. | Najjar, M., Mayers, A., Fournier-Viger, P. (2004). Goal-based Modelling of the Learner Behaviour for Scaffolding Individualised Learning Instructions. Proceedings of the 7th Intern. Conference on Computer and Information Technology (ICCIT 2004). pp: 255-262. | ||
154. | Najjar, M., Mayers, A., Fournier-Viger, P. (2004). Representing Correct/Erroneous Knowledge during Learning : A Framework for a Novel Cognitive-based Student Model. Proceedings of the 2004 Intern. Conference on Intelligent Knowledge Systems (IKS 2004). pp: 236-242. |
2020 | 1. | Fournier-Viger, P., Ganghuan, H., Zhou, M., Nouioua1, M., Liu, J. (2020). Discovering Alarm Correlation Rules for Network Fault Management. Proc. of the International Workshop on Artificial Intelligence for IT Operations (AIOPS), in conjunctions with the 18th International Conference on Service-Oriented Computing (ICSOC2020) conference, Springer LNCS series, 12 pages. [Video] |
2. | Nouioua, M., Wang, Y., Fournier-Viger, P., Lin, J.-C., Wu, J. M.-T. (2020). TKC: Mining Top-K Cross-Level High Utility Itemsets. Proc. 3rd International Workshop on Utility-Driven Mining (UDML 2020), in conjunction with the ICDM 2020 conference, IEEE ICDM workshop proceedings, to appear. [ppt] [video] | |
2019 | 3. | Lin, J. C.-W., Li, Y., Fournier-Viger, P., Djenouri, Y., Zhang, J. (2019). An Efficient Chain Structure to Mine High-Utility Sequential Patterns. Proc. 2nd International Workshop on Utility-Driven Mining (UDML 2019), in conjunction with the ICDM 2019 conference, IEEE ICDM workshop proceedings, pp. 1013-1019. |
4. | Saideep, C., Kiran, R. U., Zettsu, K., Fournier-Viger, P., Kitsuregawa, M., Reddy, P.K. (2019). Discovering Periodic Patterns in Irregular TimeSeries. Proc. 2nd International Workshop on Utility-Driven Mining (UDML 2019), in conjunction with the ICDM 2019 conference, IEEE ICDM workshop proceedings, pp. 1020-1028. |
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2018 | 5. | Fournier-Viger, P., Liu, T., Lin, J. C.-W. (2018). Football Pass Prediction using Player Locations. Proc. of the 5th Machine Learning and Data Mining for Sports Analytics (MLSA 2018), in conjunction with the PKDD 2018 conference, Springer LNAI 11330, pp. 1–7, 2019. [source code] [presentation video : HTML5 / AVI ] |
6. | Li, J., Fournier-Viger, P., Lin, J. C.-W., Truong, T. (2018). Discovering low-cost high utility patterns. 1st International Workshop on Utility-Driven Mining (UDM2018), in conjunction with the KDD 2018 conference, ACM press, 9 pages. [ppt] | |
7. | Truong, T., Tran, A., Duong, A., Le, B., Fournier-Viger, P.(2018). EHUSM: Mining High Utility Sequences with a Pessimistic Utility Model. 1st International Workshop on Utility-Driven Mining (UDM2018), in conjunction with the KDD 2018 conference (UDML 2018), 9 pages. | |
8. | Djenouri, Y., Belhadi, A., Fournier-Viger, P., Lin, C.-W. (2018) Discovering Strong Meta Association Rules using Bee Swarm Optimization. 7th Workshop on Biologically Inspired Techniques for Data Mining (BDM'18), in conjunction with the 22nd Pacific-Asia Conf. Knowledge Discovery and Data Mining (PAKDD 2018). | |
2012 | 9. | Snow, E., Moghrabi, C., Fournier-Viger, P. (2012). Assessing Procedural Knowledge in Open-ended Questions through Semantic Web Ontologies. Proc. of the 8thAustralasian Ontology Workshop (AOW2012), in conjunction with the 25th Australasian Joint Conference on Artificial Intelligence, CEUR, pp. 86-97. |
2008 | 10. | Nkambou, R, Fournier-Viger, P., Dubois, D. (2008). RomanTutor, a Tutoring System for Training Astronauts on Robotic Arm Manipulations. Proceedings of the Demonstration Program of the 9th Intern. Conference on Intelligent Tutoring Systems (ITS 2008), pp. 51-53. |
11. | Fournier-Viger, P., Nkambou, R., Mephu Nguifo, E. (2008). A Sequential Pattern Mining Algorithm for Extracting Partial Problem Spaces from Logged User Interactions. Proc. of the 3rd Intern. Workshop on Intelligent Tutoring Systems in Ill-Defined Domain: Assessment and Feedback in Ill-Defined Domains (in conjunction with ITS2008). June 23-27, Montreal, Canada. |
1. | Fournier-Viger, P. (2010), Un modèle hybride pour le support à l'apprentissage dans les domaines procéduraux et mal-définis. Ph.D. Thesis, University of Quebec in Montreal, Montreal, Canada, 184 pages. | |
2. | Fournier-Viger, P., Mephu Nguifo, E., Nkambou, R. (2009), Extraction de motifs séquentiels à partir de traces d'utilisation pour la construction automatique de modèles de tâches dans les systèmes tutoriels intelligents. Short paper. Journée thématique : Fouille de données séquentielles et ses applications, Université d'Orléans, Nov. 27, Orleans, France. | |
3. | Fournier-Viger, P. (2005). Un modèle de représentation des connaissances à trois niveaux de sémantique pour les systèmes tutoriels intelligents. M.Sc. dissertation, University of Sherbrooke, Sherbrooke, Canada, 194 pages. Chapter 4: Une introduction aux logiques de descriptions. |
1. | Fournier-Viger, P. (2019) Foreword of the Advances in Electrical and Electronic Engineering journal, volume 17, issue 1. | |
2. | Fournier-Viger, P. (2012), Intelligent tutoring systems in Ill-Defined Domains - Bibliography 2003-2012. In Paviotti, G., Rossi, P.G., Zarka, D. (Ed.) Intelligent Tutoring Systems: An overview, Pensa Multimedia, p. 153-161. (book appendix). |
Number of citations per year (based on G. Scholar, - updated 2020/12/7)
90 |
51 |
51 |
57 |
72 |
121 |
294 |
403 |
733 |
982 |
1713 |
1721 |
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