Book Chapters

1.	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.
2.	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
3.	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.
4.	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.
5.	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.

Journal Papers

1.	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, e1207 doi: 10.1002/widm.1207, 18 pages.	ISI, EI, SCI, Q1 ISSN: 1942-4787
2.	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
3.	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 (to appear)	ISI, EI, SCI, Q4 IF:_ ISSN: 0924-669X
4.	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	ISI, EI, SCI, Q1 IF: ISSN: 0952-1976
5.	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.	ISI, EI, SCI, Q1 IF: ISSN: 0952-1976
6.	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.	ISI, EI, SCI, Q1 IF: ISSN: 1932-6203
7.	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)	ISI, EI, SCI, Q2 IF: ISSN: 2095-2228
8.	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 (to appear)	ISI, EI, SCI, Q2 IF: ISSN:0219-1377
9.	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 (to appear)	ISI, EI, SCI, Q2 IF: ISSN:0219-1377
10.	Lin, C.-W., Ren, S., Fournier-Viger, P., Hong, T.-P. (2016). EHAUPM: Efficient High Average-Utility Pattern Mining with Tighter Upper-Bounds . IEEE Access, vol. 14, no. 8, IEEE, 13 pages.	ISI, EI, SCI, Q2 IF: ISSN: 2169-3536
11.	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)	ISI, EI, SCI, Q2 IF:_ ISSN: 2169-3536
12.	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, to appear.	ISI, EI, SCI, Q1 ISSN: 1474-0346
13.	Lin, C.-W., Liu, Q., Fournier-Viger, P., Hong, T.-P. (2016). PTA: An Efficient System for Transaction Database Anonymization . IEEE Access, vol. 4, pp. 6467-6479, IEEE.	ISI, EI, SCI, Q2 IF: ISSN: 2169-3536
14.	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	ISI, EI, SCI, Q2 IF: ISSN:0219-1377
15.	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, pp 873–909	ISI, EI, SCI, Q2 IF: ISSN:0219-1377
16.	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.	ISI, EI, SCI, Q4 IF: ISSN: 0925-9902
17.	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.	ISI, EI, SCI, Q1 IF: 2.07 ISSN: 1041-4347
18.	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.	ISI, EI, SCI, Q3 ISSN: 1432-7643
19.	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. 19 pages (accepted, to appear).	ISI, EI, SCI, Q3 ISSN: 1432-7643
20.	Dam, T.-L., Li, K. , Fournier-Viger, P. (2016). Chemical reaction optimization with unified tabu search for the vehicle routing problem. Soft Computing, Springer, accepted, to appear.	ISI, EI, SCI, Q3 IF: ISSN: 1432-7643
21.	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.	ISI, EI, SCI Q2 ISSN: 0952-1976
22.	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.	ISI, EI, SCI, Q1 ISSN: 1474-0346
23.	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.	ISI, EI, SCI, Q4 IF: ISSN: 0924-669X
24.	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.	ISI, EI, SCI, Q4 ISSN: 0924-669X
25.	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.	ISI, EI, SCI, Q1 IF: ISSN: 1474-0346
26.	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	ISI, EI, SCI, Q1 IF: ISSN: 0950-7051
27.	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.	ISI, EI, SCI, Q1 IF: ISSN: 0950-7051
28.	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.	ISI, EI, SCI, Q1 IF: ISSN: 0950-7051
29.	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: ISSN: 0950-7051
30.	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.	EI, SCI, Q4 IF: ISSN: 0218-1940
31.	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
32.	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.	ISI, EI, SCI, Q1 IF: 2.07 ISSN: 1041-4347
33.	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
34.	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
35.	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
36.	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
37.	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
38.	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.	ISI, EI, SCI, Q1 IF: 4.104 ISSN: 0950-7051
39.	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
40.	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
41.	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
42.	Faghihi, U., Fournier-Viger, P, Nkambou, R., Poirier, P. (2011). Identifying Causes Helps a Tutoring System to Better Adapt to Learners During Training Sessions. Journal of Intelligent Learning Systems and Application, Scientific Research Publishing, 3(3): 139-154.	IF: 1.13
43.	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.	SSCI IF: 1.34 ISSN: 1436-4522
44.	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.	ISI, EI, SCI, Q2 IF: 3.14 ISSN: 1541-1672
45.	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.	ISI, EI, SSCI IF: 0.82 ISSN: 1939-1382
46.	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 Knowledge and Learning Objects, 2:77-94.	IF: 22 ISSN: 2375-2084

Conference Papers

1.	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.
2.	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
3.	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, to appear.
4.	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, to appear.
5.	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, to appear.
6.	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, to appear.
7.	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, 9 pages.
8.	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), Springer, to appear.
9.	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.
10.	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]
11.	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.
12.	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
13.	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.
14.	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]
15.	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.
16.	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]
17.	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
18.	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.
19.	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
20.	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.
21.	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.
22.	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.
23.	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).>
24.	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. [source code]
25.	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]	* Nominated for best paper award (one of the three finalists)*
26.	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.
27.	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]	* Nominated for best poster award (one of the six finalists)*
28.	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
29.	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.
30.	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.
31.	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.
32.	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.
33.	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.
34.	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.
35.	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]
36.	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.
37.	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. [source code]
38.	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.
39.	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]
40.	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]
41.	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]	accept. rate: 6 % (long presentation)
42.	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)*
43.	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 *
44.	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.
45.	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 %
46.	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 %
47.	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.
48.	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.
49	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*
50	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.
51.	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.
52.	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 %
53.	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 *
54.	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 %
55.	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*
56.	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]
57.	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 %
58.	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 %
59.	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]
60.	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.
61.	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]
62.	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.
63.	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 %
64.	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.
65.	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)
66.	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.	accept. rate: 14 % (full paper)
67.	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]
68.	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]
69.	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]
70.	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.
71.	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%
72.	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 %
73.	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 *
74.	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 %
75.	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]
76.	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 %
77.	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)
78.	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]
79.	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.
80.	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%
81.	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.
82.	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.
83.	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]
84.	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.
85.	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.
86.	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.
87.	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.
88.	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.
89.	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.
90.	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.
91.	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%
92.	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.
93.	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%
94.	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%
95.	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.
96.	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%
97.	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.
98.	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.
99.	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.
100.	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%
101.	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.
102.	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.
103.	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.
104.	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.
105.	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.
106.	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.

Workshop Papers

1.	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.
2.	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.

Talks & Demonstrations

1.	Faghihi, U., Fournier-Viger, P., Nkambou, R. (2011), Conscious Emotional Learning Tutoring System (CELTS) : A cognitive architecture. The 6th Young Researchers Conference in Cognitive Science (Cognitio 2011): Nonhuman Minds: Animal, Artificial or Other Minds, 3-5 July, Montréal, Canada
2.	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.
3.	Fournier-Viger, P., Dubois, D., Nkambou, R., Mayers, A. (2006). Representing the Knowledge Handled in Robotized Arm Manipulations. The 3rd Young Researchers Conference in Cognitive Science (Cognitio 2006), Aug. 19-21, Montreal, Canada.

French Publications

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.
4.	Fournier-Viger, P., Mayers, A. (2005). Une représentation des connaissances selon trois perspectives (ontologique, psychopédagogique et objet d'apprentissage) pour les systèmes tutoriels intelligents. Poster, presented at the 4th IMSI (Intelligent Materials and Systems Institute) Colloquium, Oct. 26-27, Sherbrooke, Canada.
5.	Fournier-Viger, P., Mayers, A. (2003). Une méthodologie pour intégrer un contenu dynamique dans les objets d'apprentissage. Poster, presented at the 3th IMSI (Intelligent Materials and Systems Institute) Colloquium, Nov. 5-6, Sherbrooke, Canada.

Other contributions

1.

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).

Other information

• My DBLP entry
• My Google Scholar page
• Total citation count: 1359 ( Google Scholar - 2017/05/03)