Philippe

Philippe

通讯地址: (518055)
电子邮件: philfv8@yahoo.com
联系电话: 075586231832

最新简历请查阅:http://www.hitsz.edu.cn/teacher/view/id-1307.html


个人简介


菲律普•弗尼尔•维格 博士,教授,2015年入选中组部青年千人计划,2010年毕业于加拿大魁北克大学蒙特利尔分校计算机科学专业,在国际刊物和国际会议发表论文115篇,被引用780次,他是流行的SPMF开源数据挖掘库( http://www.philippe-fournier-viger.com/spmf/ )的创始人,该数据库目前可以提供超过100种数据挖掘的算法,自2010年起,这些算法已被使用于270篇专业研究论文之中。


研究方向


基础研究领域:大数据,数据挖掘,人工智能, Algorithms, Pattern Mining, SequencePrediction, SequenceAnalysis, 应用研究领域:工业创新设计


教育经历


2010计算机科学博士, 魁北克大学蒙特利尔分校 (加拿大)

2005计算机科学硕士学位, 舍布鲁克大学 (加拿大)

2003 计算机科学学士学位, 舍布鲁克大学 (加拿大)


研究与工作经历


2016-...教授 , 哈尔滨工业大学深圳研究生院

2015-2016副教授, 哈尔滨工业大学深圳研究生院

2015-present客座教授, 蒙克顿大学,加拿大

2011-2015副教授, 蒙克顿大学,加拿大

2010-2011博士后研究员, 国立成功大学,台湾


专业资质与学术兼职


Program committee memberIJKLO, PAKDD 2016, PAKDD 2015, PAKDD 2014, ACM SAC 2016, ACM SAC 2015, ACM SAC 2014, ACM SAC 2013, RAIT 2014, RAIT 2013, Top100Qi Open Forum at WIC 2012, KDIR 2015, KDIR 2014, KDIR 2013, KDIR 2012, ADMA 2014, ADMA 2013, ADMA 2012, ADMA 2011, FFDM 2012, BHI 2015, BHI 2014, BHI 2013, BI 2012, BI 2011, DMIN 2014, DMIN 2013, DMIN 2012, DMIN 2011, ICDIM 2011, FLAIRS 2014, FLAIRS 2013, FLAIRS 2012, FLAIRS 2011, Global Learn Asia Pacific 2011 - 2010, ED-MEDIA 2013, ED-MEDIA 2012, ED-MEDIA 2011, ED-MEDIA 2010, ED-MEDIA 2009, INSITE 2011, INSITE 2010, INSITE 2009, INSITE 2008, CSITEd 2007, Re-new 2013 2ème journée francophones EIAH & IA 2015, ICCCT 2015)

Invited journal reviewerACM TKDD, IEEE TKDE, IEEE Intelligent System, IEEE TLT, DMKD, Knowledge-Based Systems, Information Sciences, Engineering Applications of Artificial Intelligence, Expert Systems with Applications, Computational Intelligence, Computers and Industrial Engineering, Applied intelligence, International Journal on Artificial Intelligence Tools, Journal of Educational Data Mining, Mathematical Problems in Engineering, Sensors, International Journal of Information Technology & Decision Making, International Journal of Human Factors Modelling and Simulation, Canadian Journal of Electrical and Computer Engineering, Theoretical and Applied Climatology, Future Internet, CIT Journal of Computing and Information technology, Journal of AI and Data Mining

Invited conference reviewerCIKM 2013, CIKM 2012, ICFCA 2015, ICFCA 2014, ICFCA 2012, ICFCA 2011, SFC 2014, HAIS 2012, COSI 2014, COSI 2012, COSI 2011, EGC 2016, EGC 2012, EGC 2011, EGC 2010, ICDM DDDM 2010, CLA 2015, CLA 2014, CLA 2010, ITS 2010, ITS 2008, EDM 2013, EDM 2010, EDM 2009, EDU 2012, ICOCI 2013

Session chairPAKDD 2015, ADMA 2014, ADMA 2013, ISMIS 2012, ACM SAC 2011

Other academic serviceReviewer for Canada NSERC research proposal grants (2014) - canadian government funding agency Reviewer for FQRNT research proposal grants (2013, 2014) - Quebec province funding agency Reviewer for research grants of the Croatian Science Foundation (2014) External examiner for a M.Sc. thesis at U. of Auckland, New Zealand (2015) - M. Bian External examiner for a Ph.D thesis at U. of Sherbrooke, Canada (2014) - A. Abdessemed External examiner for a Ph.D thesis at U. of Sherbrooke, Canada (2012) - S. Wu

 


科研项目


2016-20214,000,000 RMB 1000 Young Talent (青年人计划) from Chinese Government and HITSZ "Innovative Data Mining Algorithms with Applications in Industrial design"

2013-2015500,000 RMB Discovery Grant from the National Science and Engineering Research Countil of Canada (NSERC) "Algorithms, data structures and visualization for sequence analysis and prediction" "Algorithms, data structures and vizualisation for sequence analysis and prediction"

2014MITACS research project with the nGauge company (Canada) "Semantic classification of short texts"

2014IRAP research project with the SelectBidder Company (Canada) "Prediction of online auction prices"


科研成果及奖励


20164,000,000 RMB Young Talent (青年人计划) from National Science Foundation of China

2016Oversea Talent of Shenzhen Peackock Plan (深圳市海外高层次人才孔雀计划) - Level B

2015Outstanding Young Talent - Harbin Institute of Technology, China (哈尔滨工业大学青年拔尖人才)

2016Nominated for best poster award at SAC 2016

2015最佳论文奖 at ICGEC 2015

2015Merit paper award at TAAI 2015

2015Nominated for best paper award at MLDM 2015 (among three finalists)

2014最佳论文奖 at ADMA 2014

2012Nominated for the best paper award at ISMIS 2012

2008最佳论文奖 at MICAI 2008 (1st of 363 papers)

2008Nominated for the best paper award at ITS 2008

2010-2012Post-doctoral Fellowship (FQRNT)

2006-2010Alexander Graham Bell Canada Graduate Scholarship (NSERC) Ph.D Research Fellowship (FQRNT)


发明专利



论文及著作


BOOK CHAPTERS 著作章节: 

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 期刊论文 

1. 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, Springer, 36 pages (to appear) 
2. 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. 
3. Lin, J. C.-W., Gan, W., Fournier-Viger, P., Hong, T.-P., Tseng, V. S. (2016). Efficiently Mining Uncertain High-Utility Itemsets. Soft Computing, Elsevier. (accepted, to appear). 
4. 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). 
5. 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, Elsevier. (accepted, to appear). 
6. 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 (accepted, to appear). 
7. Dam, T.-L., Li, K., Fournier-Viger, P. (2016). An efficient algorithm for mining top-rank-k frequent patterns. Applied Intelligence, Springer. 18 pages (accepted, to appear). 
8. 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. 
9. 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 (to appear). 
10. 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, accepted, to appear. 
11. 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. 
12. 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), (accepted, to appear). 
13. 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. 
14. 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. 
15. 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. 
16. 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. 
17. 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. 
18. 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. 
19. 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. 
20. 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. 
21. Faghihi, U., P. Fournier-Viger, Nkambou, R. (2012). A Computational Model for Causal Learning in Cognitive Agents, Knowledge-Based Systems, Elsevier, 30, 48-56 
22. 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. 
23. 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. 
24. 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. 
25. 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. 
26. 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. 
27. 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. 
28. 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.


会议论文及发表演说


CONFERENCE PAPERS 会议论文: 

1. 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, 15 pages, to appear 
2. 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, 15 pages, to appear 
3. 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, to appear 
4. 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 
5. 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, to appear 
6. 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, to appear 
7. 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. 
8. 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, to appear 
9. Lin, C.W., Li, T., Fournier-Viger, P., Hong, T.-P. (2016). Efficient Mining of High Average-Utility Itemsets with Multiple Minimum Thresholds. Proc. 16th Industrial Conference on Data Mining. Springer LNAI, to appear. 
10. 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, to appear. 
11. 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, to appear 
12. 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, 6 pages, to appear. 
13. 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, 10 pages, to appear. 
14. 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, 10 pages, to appear. 
15. 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. 
16. 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. 
17. 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. 
18. 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. [video] 
19. 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] 
20. 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. 
21. 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. 
22. 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. 
23. 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. 
24. 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. 
25. 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. 
26. 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. 
27. 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. 
28 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. 
29 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. 
30. 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. 
31. 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. 
32. 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. 
33. 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. 
34. 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. 
35. 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. 
36. 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. 
37. 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. 
38. 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. 
39. 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. 
40. 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. 
41. 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. 
42. 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. 
43. 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. 
44. 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. 
45. 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. 
46. 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. 
47. 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. 
48. 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. 
49. 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. 
50. 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. 
51. 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. 
52. 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. 
53. 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. 
54. 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. 
55. 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. 
56. 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. 
57. 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. 
58. 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. 
59. 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. 
60. 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. 
61. 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. 
62. 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. 
63. 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. 
64. 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. 
65. 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. 
66. 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. 
67. 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. 
68. 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. 
69. 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.
70. 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. 
71. 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. 
72. 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. 
73. 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. 
74. 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. 
75. 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.
76. 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. 
77. 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. 
78. 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. 
79. 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. 
80. 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. 
81. 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. 
82. 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. 
83. 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. 
84. 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. 
85. 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 研讨会论文: 

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.


任教和任导师经历


哈尔滨工业大学深圳研究生院招生: 
每年招收硕士研究生3名,博士研究生1名,博士后1名。 
Can supervise Ph.D and Master degree students 

蒙克顿大学 (加拿大)在读硕士研究生2名,往届硕士研究生5名 

魁北克大学蒙特利尔分校 (加拿大)在读博士研究生1名