Collaborative filtering based on workflow space

Expert Systems with Applications

Volumn 36, Issue 4, 2009, Pages 7873-7881

  Zhen, Lu ^a,b   Huang, George Q ^a   Jiang, Zuhua ^b  

^a UNIVERSITY OF HONG KONG   (Hong Kong)

^b SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Collaborative filtering; Collaborative team; Recommender system; Workflow

Indexed keywords

INFORMATION RETRIEVAL SYSTEMS; SIGNAL FILTERING AND PREDICTION;

3-DIMENSIONAL; COLLABORATIVE FILTERING; COLLABORATIVE TEAM; DAILY LIVES; GENERAL SITUATIONS; MANUFACTURING ENTERPRISE; REAL-WORLD; RECOMMENDER SYSTEM; SPACE MODELS; WORKFLOW;

MANAGEMENT;

EID: 60249099542     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.11.047     Document Type: Article

References (29)

1. Adomavicius G., Sankaranarayanan R., Sen S., and Tuzhilin A. Incorporating contextual information in recommender systems using a multidimensional approach. ACM Transactions on Information Systems 23 (2005) 103-145
2. Adomavicius G., and Tuzhilin A. Toward the next generation of recommender systems: A survey of the state of the art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17 (2005) 734-749
3. Armstrong J. Principles of forecasting: A handbook for researchers and practitioners (2001), Kluwer Academic
4. Breese, J., Heckerman, D., & Kadie, C. (1998). Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings 14th conference uncertainty in artificial intelligence.
5. Burke R. Hybrid recommender systems: Survey and experiments. User Modeling and User-adapted Interaction 12 (2002) 331-370
6. Chaudhuri S., and Dayal U. A overview of data warehousing and OLAP technology. ACM SIGMOD Record 26 1 (1997) 65-74
7. Chen Y., and Cheng L. A group recommendation system with consideration of interactions among group members. Expert Systems with Applications 34 (2008) 2082-2090
8. Chen Y., and Cheng L. A novel collaborative filtering approach for recommending ranked items. Expert Systems with Applications 34 (2008) 2396-2405
9. Goldberg D., Nichols D., Oki B., and Terry D. Using collaborative filtering to weave an information tapestry. Communications of the ACM 35 (1992) 12-13
10. Han P., Xie B., Yang F., and Shen R. A scalable P2P recommender system based on distributed collaborative filtering. Expert Systems with Applications 27 (2004) 203-210
11. Herlocker J., Konstan J., Terveen L., and Riedl J. Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems 22 (2004) 5-53
12. Hill, H., Stead, L., Rosenstein, M., & Furnas, G. (1995). Recommending and evaluating choices in a virtual community of use. In Proceedings conference human factor in computing systems.
13. Kim J., Kim H., and Cho Y. A user-oriented contents recommendation system in peer to peer architecture. Expert Systems with Applications 34 (2008) 300-312
14. Kimball R. The data warehouse toolkit (1996), John Willey and Sons Inc
15. Konstan J., Miller B., Maltz D., Herlocker J., Gordon L., and Riedl J. GroupLens: Applying collaborative filtering to usenet news. Communications of the ACM 40 3 (1997) 77-87
16. Lilien G., Kotler P., and Moorthy K. Marketing models (1992), Prentice Hall
17. McNee, S., Albert, I., Cosley, D., Gopalkrishnan, P., Lam, S., Rashid, A. (2002). On the recommending of citations for research papers. In Proceedings of CSCW 2002 (pp. 116-125). USA: New Orleans.
18. Mooney, R., & Roy, L. (2000). Content-based book recommending using learning for text categorization. In Proceedings of the ACM international conference on digital libraries (pp. 195-204). Texas, USA: San Antonia.
19. Powell M. Approximation theory and methods (1981), Cambridge University Press
20. Resnick, P., Iakovou, N., Sushak, M., Bergstrom, P., & Riedl, J. (1994). GroupLens: An open architecture for collaborative filtering of Netnews. In Proceedings conference computer supported cooperative work.
21. Rich E. User modeling via stereotypes. Cognitive Science 3 4 (1979) 329-354
22. Salton G. Automatic text processing (1989), Addison-Wesley
23. Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001). Item-based collaborative filtering recommendation algorithms. In Proceedings conference WWW10 (pp. 285-295).
24. Schafer, J., Konstan, J., & Riedl, J. (1999). Recommender systems in E-commerce. In Proceedings of 1st ACM conference on electronic commerce (pp. 158-166). Colorado, USA: Denver.
25. Shardanand, U., & Maes, P. (1995). Social information filtering: Algorithms for automating 'Word of Mouth'. In Proceedings conference human factors in computing systems.
26. Yeong B., Yoon H., and Soung H. Mining changes in customer buying behavior for collaborative recommendations. Expert Systems with Applications 28 (2005) 359-369
27. Yong S., Yum B., Song J., and Su M. Development of a recommender system based on navigational and behavioral patterns of customers in e-commerce sites. Expert Systems with Applications 28 (2005) 381-393
28. Zhen, L., & Jiang, Z. (2008). Knowledge Grid based knowledge supply model. In IEICE Transactions on Information and Systems (E91-D(4), pp. 1082-1090).
29. Zhuge H. The web resource space model (2007), Springer, Berlin