This website is an archive of the papers published in the DSPR (Data Science and Pattern Recognition) journal, which was published from 2017 to 2021 by:
Ubiquitous International Taiwan Ubiquitous Information CO., LTD.
Rm 20, 3F, No. 12, Fusing 4th Rd., Cianjhen District, Kaohsiung City, 806, Taiwan.
The original website of the DSPR journal went offline. Thus, I recovered the papers from the DSPR journal through the Internet Wayback Archive, but some papers are missing. If you have the PDF of additional papers that are missing, you may contact me. All copyrights of the journal content belong to the publisher.
Volume 1, Number 1, 2017
- Daniel Meana-Llorián, Cristian González García, Vicente García-Díaz, B. Cristina Pelayo G-Bustelo, and Nestor Garcia-Fernandez, “SenseQ: Replying questions of Social Networks users by using a Wireless Sensor Network based on sensor relationships,” Data Science and Pattern Recognition, vol. 1(1), pp. 1-12, 2017.
- Ja-Hwung Su, Wei-Yi Chang, and Vincent S. Tseng, “Integrated Mining of Social and Collaborative Information for Music Recommendation,” Data Science and Pattern Recognition, vol. 1(1), pp. 13-30, 2017.
- King-Hang Wang, Subrota K. Mondal, Ki Chan, and Xiaoheng Xie, “A Review of Contemporary E-voting: Requirements, Technology, Systems and Usability,” Data Science and Pattern Recognition, vol. 1(1), pp. 31-47, 2017.
- Hui-Huang Tsai, Mu-En Wu, and Wei-Hwa Wu, “The Information Content of Implied Volatility Skew: Evidence on Taiwan Stock Index Options,” Data Science and Pattern Recognition, vol. 1(1), pp. 48-53, 2017.
- Philippe Fournier-Viger, Jerry Chun-Wei Lin, Rage Uday Kiran, Yun Sing Koh, and Rincy Thomas, “A Survey of Sequential Pattern Mining,” Data Science and Pattern Recognition, vol. 1(1), pp. 54-77, 2017.
Volume 1, Number 2, 2017
- Chien-Ming Chen, King-Hang Wang, Tsu-Yang Wu, and Eric Ke Wang, “On the Security of a Three-party Authenticated Key Agreement Protocol based on Chaotic Maps,” Data Science and Pattern Recognition, vol. 1(2), pp. 1-10, 2017.
- Bohdan Myroniv, Cheng-Wei Wu, Yi Ren, Albert Budi Christian, Ensa Bajo, and Yu-Chee Tseng, “Analyzing User Emotions via Physiology Signals,” Data Science and Pattern Recognition, vol. 1(2), pp. 11-25, 2017.
- Raza Ul Mustafa, M. Saqib Nawaz, Javed Ferzund, M. Ikram Ullah Lali, Basit Shahzad, and Philippe Fournier-Viger, “Early Detection of Controversial Urdu Speeches from Social Media,” Data Science and Pattern Recognition, vol. 1(2), pp. 26-42, 2017.
- Nhan Vo Kim, “Some Determinants Affecting Purchase Intention of Domestic Products at Local Markets in Tien Giang Province, Vietnam,” Data Science and Pattern Recognition, vol. 1(2), pp. 43-52, 2017.
Volume 2, Number 1, 2018
- Thanh Vuong Nguyen and Kim Nhan Vo, “Designing a Homestay Tourism Model in Tien Giang Tourist Destinations,” Data Science and Pattern Recognition, vol. 2(1), pp. 1-14, 2018.
- Chien-Ming Chen, Yenyu Huang, Eric Ke Wang, and Tsu-Yang Wu*, “Improvement of a Mutual Authentication Protocol with Anonymity for Roaming Service in Wireless Communications,” Data Science and Pattern Recognition, vol. 2(1), pp. 15-24, 2018.
- Zhijin Wang*, Kaimeng Chen, and Liang He, “AsySIM: Modeling Asymmetric Social Influence for Rating Prediction,” Data Science and Pattern Recognition, vol. 2(1), pp. 25-40, 2018.
Volume 2, Number 2, 2018
- Thi Thi Zin, Pyke Tin, and Hiromitsu Hama, “Characterizing Reliability Measure for Internet of Things by Markov Queue,” Data Science and Pattern Recognition, vol. 2(2), pp. 1-10, 2018.
- Trong-The Nguyen, Jeng-Shyang Pan, Jerry Chun-Wei Lin, Thi-Kien Dao, and Thi-Xuan-Huong Nguyen, “An Optimal Node Coverage in Wireless Sensor Network Based on Whale Optimization Algorithm,” Data Science and Pattern Recognition, vol. 2(2), pp. 11-21, 2018.
Volume 3, Number 1, 2019
- Xingsi Xue, Haiyan Yang, and Jie Zhang, “Using Population-based Incremental Learning Algorithm for Matching Class Diagrams,” Data Science and Pattern Recognition, vol. 3(1), pp. 1-8, 2019
Volume 3, Number 2, 2019
- Ko-Wei Huang, Chun-Cheng Lin, Yi-Ming Lee, and Ze-Xue Wu, “A Deep Learning and Image Recognition System for Image Recognition,” Data Science and Pattern Recognition, Vol. 3(2), pp. 1–11, 2019
- Xintong Wang and Hongfeng Zhu, “A Novel Two-party Key Agreement Protocol with the Environment of Wearable Device using Chaotic Maps,” Data Science and Pattern Recognition, Vol. 3(2), pp. 12–23, 2019
- Rage Uday Kiran, Alampally Anirudh, Chennupati Saideep, Masashi Toyoda, P. Krishna Reddy, and Masaru Kitsuregawa, “Finding Periodic-Frequent Patterns in Temporal Databases using Periodic Summaries,” Data Science and Pattern Recognition, Vol. 3(2), pp. 24–46, 2019
Volume 4, Number 1, 2020
- Lina Fahed, Philippe Lenca, Yannis Haralambous, and Riwal Lefort, “Distant Event Prediction Based on Sequential Rules,” Data Science and Pattern Recognition, Vol. 4(1), pp. 1–23, 2020
- Peng Hao, Liu Lin, Ma Liya, Zhao Weiiqin, Long Yuntao, and Ma Hongyuan, “Approximate Error Estimation based Incremental Word Representation Learning,” Data Science and Pattern Recognition, Vol. 4(1), pp. 24–40, 2020
- Jeng-Shyang Pan, Xiaopeng Wang, Shu-Chuan Chu, and Trong-The Nguyen, “A Multi-group Grasshopper Optimisation Algorithm for Application in Capacitated Vehicle Routing Problem,” Data Science and Pattern Recognition, Vol. 4(1), pp. 41–56, 2020
- Chung-Ming Kuo, Nai-Chung Yang, Jeng-Yan Wu, Sheng-Chang Chen, “Histogram-Based Image Enhancement in Quasi-Spatial Domain for Compressed Image,” Data Science and Pattern Recognition, Vol. 4(1), pp. 57–71, 2020
Volume 4, Number 2, 2020
- Shu-Chuan Chu, Zhi-Gang Du, and Jeng-Shyang Pan, “Discrete Fish Migration Optimization for Traveling Salesman Problem,” Data Science and Pattern Recognition, Vol. 4(2), pp. 1–18, 2020
- Wei Song and Chaomin Huang, “Mining High Average-Utility Itemsets Based on Particle Swarm Optimization,” Data Science and Pattern Recognition, Vol. 4(2), pp. 19–32, 2020
- Shigeru Maya and Ken Ueno, “DADIL: Data Augmentation for Domain-Invariant Learning,” Data Science and Pattern Recognition, Vol. 4(2), pp. 33–49, 2020
- Philippe Fournier-Viger, Jiaxuan Li, Jerry Chun-Wei Lin, and Tin Truong Chi, “Discovering Low-Cost High Utility Patterns,” Data Science and Pattern Recognition, Vol. 4(2), pp. 50–64, 2020
- Tin Truong, Anh Tran, Hai Duong, Bac Le, and Philippe Fournier-Viger, “EHUSM: Mining High Utility Sequences with a Pessimistic Utility Model,” Data Science and Pattern Recognition, Vol. 4(2), pp. 65–83, 2020
Volume 5, Number 1, 2021
- Vidushi Chaudhary, Anand Deshbhratar, Vijayanand Kumar, and Dibyendu Paul, “Time Series Based LSTM Model to Predict Air Pollutant’s Concentration for Prominent Cities in India,” Data Science and Pattern Recognition, Vol. 5(1), pp. 1–15, 2021
- Vincent Mwintieru Nofong and Hamidu Abdel-Fatao, “Towards Predicting the Occurrence Times of Emerging and Decaying Patterns,” Data Science and Pattern Recognition, Vol. 5(1), pp. 16–26, 2021
Volume 5, Number 2, 2021
- Thanh-Tuan Nguyen, Wan-Wei Lin, Que-Son Vo, and Chin-Shiuh Shieh, Delay Aware Routing based on Queuing Theory for Wireless Sensor Networks, Data Science and Pattern Recognition, Vol. 5(2), pp. 1–10, 2021
- Chung-Ming Kuo, Chaur-Heh Hsieh, Shen-Cha Tseng, and Jeng-Yan Wu, Stacked Deep Convolution Network for Image Super-Resolution, Data Science and Pattern Recognition, Vol. 5(2), pp. 11–27, 2021
- Jin-Liang Zhou, Shu-Chuan Chu, Yan-Jun Peng, Kuan-Chun Huang, and Jeng-Shyang Pan, An Advanced Clustering Algorithm based on k-means and Phasmatodea Population Evolution Algorithm, Data Science and Pattern Recognition, Vol. 5(2), pp. 28–38, 2021
Editorial board
| Editor-in-Chief | |
| Jerry Chun-Wei Lin (FIET) | Western Norway University of Applied Sciences, Norway |
| Philippe Fournier-Viger | Shenzhen University – Shenzhen, China |
| Advisory Board Member | |
| Ajith Abraham | Machine Intelligence Research Labs, USA |
| Longbing Cao | University of Technology Sydney, Australia |
| Han-Chieh Chao (FIET) | National Dong Hwa University (President), Taiwan |
| Hamido Fujita | Iwate Prefectural University, Japan |
| Tzung-Pei Hong | National University of Kaohsiung, Taiwan |
| Engelbert Mephu Nguifo | Université Blaise Pascal – Clermont Ferrand, France |
| Ponnuthurai Nagaratnam Suganthan (FIEEE) | Nanyang Technical University, Singapore |
| Roger Nkambou | Université du Québec à Montréal, Canada |
| Jeng-Shyang Pan (FIET) | Shandong University of Science and Technology, China |
| Vaclav Snasel | VŠB-Technical University of Ostrava, Czech Republic |
| Ljiljana Trajkovic (FIEEE) | Simon Fraser University, Canada |
| Vincent S. Tseng (FIEEE) | National Chiao-Tung University, Taiwan |
| Shyue-Liang Wang (FIET) | National University of Kaohsiung, Taiwan |
| Sebastian Ventura | University of Cordoba, Spain |
| Philip S. Yu (FIEEE) | University of Illinois at Chicago, USA |
| Osmar Zaïane | University of Alberta, Canada |
| Associate Editor | |
| Chien-Ming Chen | Shangdong University of Science and Technology |
| Chun-Hao Chen | Tamkang University, Taiwan |
| Vicente Garcia Diaz | University of Oviedo, Spain |
| Pinar Karagoz | Middle East Technical University, Turkey |
| Yun Sing Koh | University of Auckland, New Zealand |
| Ivan Lee | University of South Australia, Australia |
| João Mendes Moreira | University of Porto, Portugal |
| I-Hsien Ting | National University of Kaohsiung, Taiwan |
| Chun-Wei Tsai | National Chung-Hsing University, Taiwan |
| Bay Vo | Ho Chi Minh City University of Technology, Vietnam |
| Miroslav Voznak | VŠB-Technical University of Ostrava, Czech Republic |
| Tsu-Yang Wu | Shangdong University of Science and Technology |
| Mu-En Wu | Soochow University, Taiwan |
| Xingsi Xue | Fujian University of Technology, China |
| Unil Yun | Sejong University, Korea |
| Hao Peng | Beihang University, China |
| Publicity Editor | |
| Jimmy Ming-Tai Wu | Shandong University of Science and Technology, China |
| Usman Ahmed | Western Norway University of Applied Sciences, Norway |
Aims and scope
Data science and analytics has emerged as an important research topic in recent decades, with applications in many fields such as market basket analysis, social networks, the Internet of Things and cloud computing. Pattern recognition is also a very active research area in computer science and information theory, which is increasingly popular in recent years. The primary objective of the Data Science and Pattern Recognition (DSPR) journal is to give the opportunity to researchers, scientists, industry practitioners, and professionals to publish outstanding work in these fields. The journal welcomes manuscripts describing experimental and theoretical findings both on data science and pattern recognition, and encourages the application of theoretical models in real-life applications. The journal also welcomes the submission of survey papers that provides a detailed overview of specific research areas.
Topics of relevance include all aspects of the scientific foundations, technologies, theories, and applications in the fields of data science and pattern recognition, including but not limited to:
- Data mining
- Knowledge modeling and visualization
- Machine learning and deep learning
- Database management and query processing
- Social network analytics, behavior analytics and text analytics
- Big data mining and cloud computing
- Security, trust and privacy issues
- Bioinformatics
- Recomender systems
- Pattern recognition
- Image or signal processing
- Artificial intelligence and optimization methods
- Innovative software for data science or pattern recognition
