Nearest-biclusters collaborative filtering with constant values

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

Volumn 4811 LNAI, Issue , 2007, Pages 36-55

  Symeonidis, Panagiotis ^a   Nanopoulos, Alexandras ^a   Papadopoulos, Apostolos ^a   Manolopoulos, Yannis ^a  

^a ARISTOTLE UNIVERSITY OF THESSALONIKI   (Greece)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; DATA STRUCTURES; INFORMATION ANALYSIS; PROBLEM SOLVING;

BICLUSTERING; COLLABORATIVE FILTERING (CF) SYSTEMS; INFORMATION OVERLOAD;

COMPUTER SUPPORTED COOPERATIVE WORK;

EID: 38549094007     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-77485-3_3     Document Type: Conference Paper

References (29)

1. Ben-Dor, A., Chor, B., Karp, R., Yakhini, Z.: Discovering local structure in gene expression data: The order-preserving submatrix problem. Journal of Computational Biology 10(3/4), 373-384 (2003)
2. Cheng, Y., Church, G.: Biclustering of expression data. In: Proceedings of the ISMB Conference, pp. 93-103 (2000)
3. Deshpande, M., Karypis, G.: Item-based top-n recommendation algorithms. ACM Transactions on Information Systems 22(1), 143-177 (2004)
4. Dhillon, I.S.: Co-clustering documents and words using bipartite spectral graph partitioning. In: Proceedings of the ACM SIGKDD Conference (2001)
5. Dhillon, I.S., Mallela, D.S., Modha, S.: Information theoretic co-clustering. In: Proceedings of the ACM SIGKDD Conference (2003)
6. Goldberg, D., Nichols, D., Brian, M., Terry, D.: Using collaborative filtering to weave an information tapestry. ACM Communications 35(12), 61-70 (1992)
7. Hartigan, J.A.: Direct clustering of a data matrix. Journal of the American Statistical Association 67(337), 123-129 (1972)
8. Herlocker, J., Konstan, J., Borchers, A., Riedl, J.: An algorithmic framework for performing collaborative filtering. In: Proceedings of the ACM SIGIR Conference, pp. 230-237 (1999)
9. Herlocker, J., Konstan, J., Riedl, J.: An empirical analysis of design choices in neighborhood-based collaborative filtering algorithms. Information Retrieval 5(4), 287-310 (2002)
10. Herlocker, J., Konstan, J., Terveen, L., Riedl, J.: Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems 22(1), 5-53 (2004)
11. Hofmann, T., Puzicha, J.: Latent class models for collaborative filtering. In: Proceedings of the IJCAI Conference (1999)
12. Ihmels, J., Bergmann, S., Barkai, N.: Defining transcription modules using large-scale gene expression data. Bioinformatics 20(13), 1993-2003 (2004)
13. Karypis, G.: Evaluation of item-based top-n recommendation algorithms. In: Proceedings of the ACM CIKM Conference, pp. 247-254 (2001)
14. Long, B., Zhang(Mark), Z., Yu, P.S.: Co-clustering by block value decomposition. In: KDD 2005. Proceeding of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining, pp. 635-640. ACM Press, New York (2005)
15. Madeira, S., Oliveira, A.: Biclustering algorithms for biological data analysis: a survey. ACM Transactions on Computational Biology and Bioinformatics 1, 24-45 (2004)
16. McLauglin, R., Herlocher, J.: A collaborative filtering algorithm and evaluation metric that accurately model the user experience. In: Proceedings of the ACM SIGIR Conference, pp. 329-336 (2004)
17. Mirkin, B.: Mathematical classification and clustering. Kluwer Academic Publishers, Dordrecht (1996)
18. Mobasher, B., Dai, H., Luo, T., Nakagawa, M.: Improving the effectiveness of collaborative filtering on anonymous web usage data. In: Proceedings of the Workshop Intelligent Techniques for Web Personalization, pp. 53-60 (2001)
19. Murali, T., Kasif, S.: Extracting conserved gene expression motifs from gene expression data. In: Proceedings of the Pacific Symposim on Biocompomputing Conference, vol. 8, pp. 77-88 (2003)
20. Prelic, A., et al.: A systematic comparison and evaluation of biclustering methods for gene expression data. Technical Report (2005)
21. Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: Grouplens: An open architecture for collaborative filtering on netnews. In: Proceedings of the Computer Supported Collaborative Work Conference, pp. 175-186 (1994)
22. Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Analysis of recommendation algorithms for e-commerce. In: Proceedings of the ACM Electronic Commerce Conference, pp. 158-167 (2000)
23. Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Application of dimensionality reduction in recommender system-a case study. In: ACM WebKDD Workshop (2000)
24. Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. In: Proceedings of the WWW Conference, pp. 285-295 (2001)
25. Symeonidis, P., Nanopoulos, A., Papadopoulos, A., Manolopoulos, Y.: Collaborative filtering process in a whole new light. In: Proc. IDEAS conf., pp. 29-36 (2006)
26. Tanay, A., Sharan, R., Kupiec, M., Shamir, R.: Revealing modularity and organization in the yeast molecular network by integrated analysis of highly heterogeneous genomewide data. In: Proceedings of the National Academy of Science conference, pp. 2981-2986 (2004)
27. Tanay, A., Sharan, R., Shamir, R.: Discovering statistically signifnicant biclusters in gene expression data. In: Proceedings of the ISMB conference (2002)
28. Ungar, L., Foster, D.: A formal statistical approach to collaborative filtering. In: Proceedings of the CONALD Conference (1998)
29. Xue, G., Lin, C., Yang, Q., et al.: Scalable collaborative filtering using cluster-based smoothing. In: Proceedings of the ACM SIGIR Conference, pp. 114-121 (2005)