39. Cheng-Wei Wu, Yun-Wei Lin, Ming-Ta Chen,"A Fast Algorithm for Deriving Frequent Itemsets.",Proceedings of Conference on Technologies and Applications of Artificial Intelligence (TAAI), 2021.

38. Cheng-Wei Wu, Yun-Wei Lin, Sheng Wei Ciou, Yen Fu Lin, Ji-Hong Cheng, "一個從高效益封閉項目集還原高效益項目的高效能方法.",Proceedings of Conference on Technologies and Applications of Artificial Intelligence (TAAI), 2021.

37. Cheng-Wei Wu, Yen-Fu Lin, Yun-Wei Lin, Ji-Hong, "一個從封閉頻繁序列還原頻繁序列的高效能方法.", Proceedings of Conference on Technologies and Applications of Artificial Intelligence (TAAI), 2021.

36. Wei-Chun Chang, Cheng-Wei Wu, Richard Yi-Chia Tsai, Kate Ching-Ju Lin, Yu-Chee Tseng, “Eye on You: Fusing Gesture Data from Depth Camera and Inertial Sensors for Person Identification,” IEEE International Conference on Robotics and Automation (ICRA), 2018. (Top Conference in Robotics Field).

35. Cheng-Wei Wu, Hua-Zhi Yang, Bajo Ensa, Yi Ren, Yan-Ann Cheng, Yu-Chee Tseng, “Apply Machine Learning to Head-motion Recognition using Wearables," Proceedings of International Conference on Awareness Science and Technology (iCAST), 2017.

34. Yi Ren, Tsung-Han Tsai, Ji-Cheng Huang, Cheng-Wei Wu, Yu-Chee Tseng, “Flowtable-Free Routing for Data Center Networks: A Software-Defined Approach,” Proceedings of IEEE Global Communications Conference (GlobeCom), 2017.

33. Yi Ren, Tsung-Han Tsai, Ji-Cheng Huang, Cheng-Wei Wu, Yu-Chee Tseng, “Flowtable-Free Routing for Data Center Networks: A Software-Defined Approach,” Proceedings of IEEE Global Communications Conference (GlobeCom), 2017.

32. “iToy: A LEGO-like Solution for Small Scale IoT Applications,” Proceedings of Asia-Pacific Network Operations and Management Symposium (APONMS), pp. 307-310, 2017. (Poster Session)

31. Bogdan Myroniv, Yi Ren, Cheng-Wei Wu, Yu-Chee Tseng, “Analysis of Users’ Emotions Through Physiology,” Proceedings of International Conference on Genetic and Evolutionary Computing (ICGEC), pp 136-143, 2017. (Best Paper Award)

30. Deeporn Mungtavesinsuk, Yan-Ann Cheny, Cheng-Wei Wu, Ensa Bajo, Hsin-Wei Kao, Yu-Chee Tseng, “Using Nonverbal Information for Conversation Partners Inference by Wearable Devices,” Proceedings of EAI International Conference on IoT as a Service (IoTaaS), 2017. (Best Paper Award)

29. Xin Zhang, Cheng-Wei Wu, Philippe Fournier-Viger, Lan-Da Van, Yu-Chee Tseng, “Analyzing Students’ Attention in Class Using Wearable Devices,” to appear in IEEE 18th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM), 2017.

28. Yi-Chia Tsai, Yu-Da Cheng, Cheng-Wei Wu, Yu-Chee Tseng, Yueh-Ting Lai, Wan-Hsun Hu, Jeu-Yih Jeng, “Time-Dependent Smart Data Pricing Based on Machine Learning,” Proceedings of Canadian Conference on Artificial Intelligence (CAIAC), Lecture Notes in Computer Science, Vol. 10233, pp. 103-108, 2017.

27. Philippe Fournier-Viger, Souleymane Zida, Jerry Chun-Wei Lin, Cheng-Wei Wu, Vincent S. Tseng, “Efficient Closed High-utility Itemset Mining,” Proceedings of ACM International Symposium on Applied Computing (SAC), pp. 898-900, 2016.

26. Philippe Fournier-Viger, Souleymane Zida, Jerry Chun-Wei Lin, Cheng-Wei Wu, Vincent S. Tseng, “EFIM-Closed: Fast and Memory Efficient Discovery of Closed High-Utility Itemsets,” Proceedings of The 12th International Conference on Machine Learning and Data Mining in Pattern Recognition (MLDM), pp. 199-213, 2016.

25. Philippe Fournier-Viger, Chun-Wei Lin, Cheng-Wei Wu,Vincent S. Tseng, Usef Faghihi, “Mining Minimal High-Utility Itemsets,” Proceedings of The 27th International Conference on Database and Expert Systems Applications (DEXA), pp. 88-101, 2016.

24. Vincent S. Tseng, Cheng-Wei Wu, Jun-Han Lin, Philippe Fournier-Viger, “UP-Miner: A Utility Pattern Mining Toolbox”, Proceedings of International Conference on Data Mining (ICDM), Demo Track, pp. 1656-1659, 2015.

23. Cheng-Wei Wu, Philippe Fournier-Viger, Jia-Yuan Gu, and Vincent S. Tseng, “Mining Closed+ High Utility Itemsets without Candidate Generation”, Proceedings of Conference on Technologies and Applications of Artificial Intelligence (TAAI), International Track, pp. 187-194, 2015. (Merit Paper Award)

22. Ying Chun Lin, Cheng-Wei Wu, Vincent S. Tseng, Kun-Ta Chuang, “Mining High Utility Itemsets in Big Data,” Proceedings Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 649-661, 2015. [Acceptance Rate: 22.22%] (Top Conference in Data Mining for Asia Pacific Area)

21. Souleymane Zida, Philippe Fournier-Viger, Cheng-Wei Wu, Jerry Chun-Wei Lin, Vincent S. Tseng, “Efficient Mining of High-utility Sequential Rules”, Proceedings of International Conference on Machine Learning and Data Mining in Pattern Recognition (MLDM), pp 157-171, 2015. (Nominated for Best Paper Award)

20. Moteza Zihayat, Cheng-Wei Wu, Aijun An and Vincent S. Tseng, “Mining High Utility Sequential Patterns from Evolving Data Streams”, Proceedings of the ASE Big Data & Social Informatics, Article No. 52, 2015.

19. Souleymane Zida, Philippe Fournier-Viger, Jerry Chun-Wei Lin, Cheng-Wei Wu, Vincent S. Tseng, “EFIM: A Highly Efficient Algorithm for High-Utility Itemset Mining”, Proceedings of the Mexican International Conference on Artificial Intelligence (MICAI), Springer LNAI 9413, pp. 530-546, 2015.

18. Philippe Fournier-Viger, Cheng-Wei Wu, Vincent S. Tseng, “New Concise Representations of High Utility Itemsets using Generator Patterns”, Proceedings of International Conference on Advanced Data Mining and Applications (ADMA), pp. 30-43, 2014. (Best Paper Award)

17. Chia Hua Li, Cheng-Wei Wu, Vincent S. Tseng, “Efficient Vertical Mining of High Utility Quantitative Itemsets”, Proceedings of International Conference on Granular Computing (GrC), pp. 155-160, 2014.

16. Philippe Fournier-Viger, Cheng-Wei Wu, Antonio Gomariz, Vincent S. Tseng, “VMSP: Efficient Vertical Mining of Maximal Sequential Patterns”, Proceedings of Canadian Conference on AI (CAAI), pp. 83-94, 2014.

15. Philippe Fournier-Viger, Cheng-Wei Wu, Souleymane Zida, Vincent S. Tseng, “FHM: Faster High-Utility Itemset Mining Using Estimated Utility Co-occurrence Pruning”, Proceedings of International Symposium on Methodologies for Intelligent Systems (ISMIS), pp. 83-92, 2014.

14. Cheng Wei Wu, Yu-Feng Lin, Philip S. Yu, Vincent S. Tseng, “Mining High Utility Episodes in Complex Event Sequences”, Proceedings of ACM SIG KDD International Conference on Knowledge Discovery and Data Mining, pp.536-544, 2013. [Full Paper, Oral Presentation, Acceptance Rate: 126/726 = 17.35%] (Top Conference in Data Mining)

13. Philippe Fournier-Viger, Cheng-Wei Wu, Vincent S. Tseng, “Mining Maximal Sequential Patterns without Candidate Maintenance”, Proceedings of the International Conference on Advanced Data Mining and Applications (ADMA), pp. 16-9180, 2013.

12. Cheng-Wei Wu, Shun-Chieh Lin, Huan-Wen Tsai, Vincent S. Tseng, ”A Community-based Service Recommendation System”, Proceedings of Annual Conference of the Japanese Society for the Artificial Intelligence (JSAI), 2013.

11. Cheng Wei Wu, Bai-En Shie, Philip S. Yu, Vincent S. Tseng, “Mining Top-K High Utility Itemsets”, Proceedings of ACM SIG KDD Conference on Knowledge Discovery and Data Mining, pp. 78-86, 2012. [Full Paper, Oral Presentation, Acceptance Rate: 133/755 = 17.61%] (Top Conference in Data Mining)

10. Philippe Fournier-Viger, Cheng-Wei Wu, Vincent S. Tseng, “Mining Sequential Rules Common to Several Sequences with the Window Size Constraint”, Proceedings of Canadian Conference on AI (CAAI), pp. 299-304, 2012.

9. Philippe Fournier-Viger, Cheng-Wei Wu, Vincent S. Tseng, “Mining Top-K Association Rules”, Proceedings of the 25th Canadian Conference on AI (CAAI), pp. 61-73, 2012.

8. Cheng-Wei Wu, Philippe Fournier-Viger, Philip S. Yu, Vincent S. Tseng, “Efficient Mining of a Concise and Lossless Representation of High Utility Itemsets”, Proceedings of International Conference on Data Mining (ICDM), pp. 824-833, 2011. [Full Paper, Oral Presentation, Acceptance Rate: 101/806 = 12.53%] (Top Conference in Data Mining)

7. Show-Jane Yen, Cheng-Wei Wu, Yue-Shi Lee, Vincent S. Tseng, “A Fast Algorithm for Mining Frequent Closed Itemsets over Stream Sliding Window”, Proceedings of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 996-1002, 2011.

6. Ja-Hwung Su, Cheng-Wei Wu, Shao-Yu Fu, Yu-Feng Lin, Wei-Yi Chang, I-Bin Liao, Kuo-Wei Chang, Vincent. S. Tseng. “Empirical Analysis of Content-based Music Retrieval for Music Identification,” Proceedings of International Conference on Multimedia Technology (ICMT), pp. 3516 - 3519, 2011.

5. Vincent S. Tseng, Cheng-Wei Wu, Bai-En Shie, Philip S. Yu, “UP-Growth: An Efficient Algorithm for High Utility Itemsets Mining”, Proceedings of ACM SIG KDD Conference on Knowledge Discovery and Data Mining, pp. 253-262, 2010. [Full Paper, Oral Presentation, Acceptance Rate: 77/578 = 13.32%] (Top Conference in Data Mining)

4. Show-Jane Yen, Yue-Shi Lee, Chiu-Kuang Wang, Cheng-Wei Wu, Liang-Yu Ouyang, “The Studies of Mining Frequent Patterns Based on Frequent Pattern Tree”, Proceedings of Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 232-24, 2009. [Full Paper, Oral Presentation, Acceptance Rate: 11.54%] (Top Conference in Data Mining for Asia Pacific Area)

3. Show-Jane Yen, Yue-Shi Lee, Cheng-Wei Wu and Chin-Lin Lin, “An Efficient Algorithm for Maintaining Frequent Closed Itemsets over Data Streams”, Proceedings of International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE), pp. 767-776, 2009. (Part of the Lecture Notes in Computer Science book series, Vol. 5579)

2. Show-Jane Yen, Yue-Shi Lee, Chiu-Kuang Wang, Cheng-Wei Wu, “The Combinations of Frequent Pattern Tree and Candidate Generation for Mining Frequent Patterns”, Proceedings of International Symposium on Database Theory and Application (DTA), pp. 43-45, 2008.

1. Yue-Shi Lee, Show-Jane Yen, Chiu-Kuang Wang, Cheng-Wei Wu, “A Efficient Approach for Mining Frequent Patterns Based on Traversing a Frequent Pattern Tree”, Proceedings of International Conference on Computer Science and Software Engineering (CSSE), pp. 354-357, 2008.