Incorporating concept hierarchies into usage mining based recommendations

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4811 LNAI, Issue , 2007, Pages 110-126

  Bose, Amit ^a   Beemanapalli, Kalyan ^a   Srivastava, Jaideep ^a   Sahar, Sigal ^b  

^a UNIVERSITY OF MINNESOTA   (United States)

^b INTEL CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION MANAGEMENT; MATHEMATICAL MODELS; WEBSITES;

CONCEPT HIERARCHIES; RECOMMENDATION SYSTEM; SCORING SYSTEM; WEB-CONTENT MANAGEMENT SYSTEMS;

DATA MINING;

EID: 38549167064     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-77485-3_7     Document Type: Conference Paper

References (29)

1. Adomavicius, G., Tuzhilin, A.: Towards 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 (June 2005)
2. Anderson, C., Domingos, P., Weld, D.: Relational Markov models and their application to adaptive Web navigation. In: Proceedings of 8th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining, Edmonton, Canada, pp. 143-152. ACM Press, New York (2002)
3. Cluto, http://www-users.cs.umn.edu/karypis/cluto/index.html
4. Cooley, R., Mobasher, B., Srivastava, J.: Data preparation for mining World Wide Web browsing patterns. Journal of Knowledge and Information Systems 1(1) (1999)
5. Cooley, R., Srivastava, J., Mobasher, B.: Web Mining: Information and pattern discovery on the world-wide web. In: 9th IEEE International Conference on Tools with Artificial Intelligence (November 1997)
6. Cosley, D., Lawrence, S., Pennock, D.M.: REFEREE: An open framework for practical testing of recommender systems using research index. In: Bressan, S., Chaudhri, A.B., Lee, M.L., Yu, J.X., Lacroix, Z. (eds.) CAiSE 2002 and VLDB 2002. LNCS, vol. 2590, Springer, Heidelberg (2003)
7. DeLong, C., Desikan, P., Srivastava, J. (User Sensitive Expert Recommendation): What Non-Experts NEED to Know, WebKDD 2005 Workshop. In: Nasraoui, O., Zaïane, O., Spiliopoulou, M., Mobasher, B., Masand, B., Yu, P.S. (eds.) WebKDD 2005. LNCS (LNAI), vol. 4198, Springer, Heidelberg (2006)
8. Ding, C., He, X., Zha, H., Gu, M., Simon, H.: Spectral min-max cut for graph partitioning and data clustering. Technical Report TR-2001-XX, Lawrence Berkeley National Laboratory, University of California, Berkeley, CA (2001)
9. Ganter, B., Wille, R.: Formal Concept Analysis - Mathematical Foundations. Springer, Heidelberg (1999)
10. Google Directory, http://directory.google.com
11. Gusfield, D.: Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology. Cambridge University Press, Cambridge (1997)
12. Gündüz, S., Ozsu, M.T.A.: Web Page Prediction Model Based on Click-Stream Tree Representation of User Behavior. In: Proceedings of the 9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 535-540. ACM Press, New York (2003)
13. Jia, L., Zaïane, O.R.: Combining Usage, Content, and Structure Data to Improve Web Site Recommendation. In: Bauknecht, K., Bichler, M., Pröll, B. (eds.) EC-Web 2004. LNCS, vol. 3182, pp. 305-315. Springer, Heidelberg (2004)
14. Lee, J.H., Kim, M.H., Lee, Y.J.: Information retrieval based on conceptual distance in ISA hierarchies. Journal of Documentation 49(2), 188-207 (1993)
15. Mobasher, B., Cooley, R., Srivastava, J.: Creating adaptive web sites through usage-based clustering of URLs. In: Knowledge and Data Engineering workshop (1999)
16. Mobasher, B., Dai, H., Luo, T., Nakagawa, M.: Effective Personalization Based on Association Rule Discovery from Web Usage Data. In: Proceedings of the 3rd ACM Workshop on Web Information and Data Management (WIDM 2001)/International Conference on Information and Knowledge Management (CIKM 2001), Atlanta GA (November 2001)
17. Mobasher, B., Dai, H., Luo, T., Nakagawa, M.: Using sequential and non-sequential patterns for predictive web usage mining tasks. In: ICDM 2002. Proceedings of the IEEE International Conference on Data Mining, Maebashi City, Japan (December 2002)
18. Nakagawa, M., Mobasher, B.: Impact of site characteristics on recommendation models based on association rules and sequential patterns. In: Proceedings of the IJCAI (2003)
19. Nakagawa, M., Mobasher, M.: A hybrid web personalization model based on site connectivity. In: Zaïane, O.R., Srivastava, J., Spiliopoulou, M., Masand, B. (eds.) WEBKDD 2002 - Mining Web Data for Discovering Usage Patterns and Profiles. LNCS (LNAI), vol. 2703, pp. 59-70. Springer, Heidelberg (2003)
20. Nasraoui, O., Frigui, H., Joshi, A., Krishnapuram, R.: Mining Web Access Logs Using Relational Competitive Fuzzy Clustering. In: IFSA 1999. Proceedings of the 8th International Fuzzy Systems Association World Congress, Taipei (August 1999)
21. Pierrakos, D., Paliouras, G.: Exploiting Probabilistic Latent Information for the Construction of Community Web Directories. In: Ardissono, L., Brna, P., Mitrović, A. (eds.) UM 2005. LNCS (LNAI), vol. 3538, pp. 89-98. Springer, Heidelberg (2005)
22. Rada, R., Bicknell, E.: Ranking documents with a thesaurus. JASIS 40(5), 304-310 (1989)
23. Rada, R., Mili, H., Bicknell, E., Blettner, M.: Development and application of a metric on semantic nets. IEEE Transaction on Systems, Man, and Cybernetics 19(1), 17-30 (1989)
24. Resnik, P.: Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language. Journal of Artificial Intelligence Research 11, 95-130 (1999)
25. Sieg, A., Mobasher, B., Burke, R.: Inferring User's Information Context: Integrating User Profiles and Concept Hierarchies. In: Proceedings of the 2004 Meeting of the International Federation of Classification Societies, Chicago IL (2004)
26. Srivastava, J., Cooley, R., Deshpande, M., Tan, P.N.: Web usage mining: Discovery and applications of usage patterns from web data. SIGKDD Explorations 1(2), 12-23 (2000)
27. University of Minnesota College of Liberal Arts, http://www.class.umn.edu
28. Zhu, J., Hong, J., Hughes, J.G.: Using Markov Models for website link prediction. In: Proceedings of the 13th ACM Conference on Hypertext and Hypermedia, pp. 169-170. ACM Press, New York (2002)
29. Yahoo! Directory, http://dir.yahoo.com