next up previous
Next: About this document ... Up: Item-based Collaborative Filtering Recommendation Previous: Conclusion

Bibliography

1
Aggarwal, C. C., Wolf, J. L., Wu K., and Yu, P. S. (1999). Horting Hatches an Egg: A New Graph-theoretic Approach to Collaborative Filtering. In Proceedings of the ACM KDD'99 Conference. San Diego, CA. pp. 201-212.

2
Basu, C., Hirsh, H., and Cohen, W. (1998). Recommendation as Classification: Using Social and Content-based Information in Recommendation. In Recommender System Workshop '98. pp. 11-15.

3
Berry, M. W., Dumais, S. T., and O'Brian, G. W. (1995). Using Linear Algebra for Intelligent Information Retrieval. SIAM Review, 37(4), pp. 573-595.

4
Billsus, D., and Pazzani, M. J. (1998). Learning Collaborative Information Filters. In Proceedings of ICML '98. pp. 46-53.

5
Brachman, R., J., Khabaza, T., Kloesgen, W., Piatetsky-Shapiro, G., and Simoudis, E. 1996. Mining Business Databases. Communications of the ACM, 39(11), pp. 42-48, November.

6
Breese, J. S., Heckerman, D., and Kadie, C. (1998). Empirical Analysis of Predictive Algorithms for Collaborative Filtering. In Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence, pp. 43-52.

7
Cureton, E. E., and D'Agostino, R. B. (1983). Factor Analysis: An Applied Approach. Lawrence Erlbaum associates pubs. Hillsdale, NJ.

8
Deerwester, S., Dumais, S. T., Furnas, G. W., Landauer, T. K., and Harshman, R. (1990). Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science, 41(6), pp. 391-407.

9
Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P., and Uthurusamy, R., Eds. (1996). Advances in Knowledge Discovery and Data Mining. AAAI press/MIT press.

10
Goldberg, D., Nichols, D., Oki, B. M., and Terry, D. (1992). Using Collaborative Filtering to Weave an Information Tapestry. Communications of the ACM. December.

11
Good, N., Schafer, B., Konstan, J., Borchers, A., Sarwar, B., Herlocker, J., and Riedl, J. (1999). Combining Collaborative Filtering With Personal Agents for Better Recommendations. In Proceedings of the AAAI-'99 conference, pp 439-446.

12
Herlocker, J., Konstan, J., Borchers, A., and Riedl, J. (1999). An Algorithmic Framework for Performing Collaborative Filtering. In Proceedings of ACM SIGIR'99. ACM press.

13
Herlocker, J. (2000). Understanding and Improving Automated Collaborative Filtering Systems. Ph.D. Thesis, Computer Science Dept., University of Minnesota.

14
Hill, W., Stead, L., Rosenstein, M., and Furnas, G. (1995). Recommending and Evaluating Choices in a Virtual Community of Use. In Proceedings of CHI '95.

15
Karypis, G. (2000). Evaluation of Item-Based Top-N Recommendation Algorithms. Technical Report CS-TR-00-46, Computer Science Dept., University of Minnesota.

16
Konstan, J., Miller, B., Maltz, D., Herlocker, J., Gordon, L., and Riedl, J. (1997). GroupLens: Applying Collaborative Filtering to Usenet News. Communications of the ACM, 40(3), pp. 77-87.

17
Ling, C. X., and Li C. (1998). Data Mining for Direct Marketing: Problems and Solutions. In Proceedings of the 4th International Conference on Knowledge Discovery and Data Mining, pp. 73-79.

18
Peppers, D., and Rogers, M. (1997). The One to One Future : Building Relationships One Customer at a Time. Bantam Doubleday Dell Publishing.

19
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., and Riedl, J. (1994). GroupLens: An Open Architecture for Collaborative Filtering of Netnews. In Proceedings of CSCW '94, Chapel Hill, NC.

20
Resnick, P., and Varian, H. R. (1997). Recommender Systems. Special issue of Communications of the ACM. 40(3).

21
Reichheld, F. R., and Sasser Jr., W. (1990). Zero Defections: Quality Comes to Services. Harvard Business School Review, 1990(5): pp. 105-111.

22
Reichheld, F. R. (1993). Loyalty-Based Management. Harvard Business School Review, 1993(2): pp. 64-73.

23
Sarwar, B., M., Konstan, J. A., Borchers, A., Herlocker, J., Miller, B., and Riedl, J. (1998). Using Filtering Agents to Improve Prediction Quality in the GroupLens Research Collaborative Filtering System. In Proceedings of CSCW '98, Seattle, WA.

24
Sarwar, B. M., Karypis, G., Konstan, J. A., and Riedl, J. (2000). Application of Dimensionality Reduction in Recommender System-A Case Study. In ACM WebKDD 2000 Workshop.

25
Sarwar, B. M., Karypis, G., Konstan, J. A., and Riedl, J. (2000). Analysis of Recommendation Algorithms for E-Commerce. In Proceedings of the ACM EC'00 Conference. Minneapolis, MN. pp. 158-167

26
Schafer, J. B., Konstan, J., and Riedl, J. (1999). Recommender Systems in E-Commerce. In Proceedings of ACM E-Commerce 1999 conference.

27
Shardanand, U., and Maes, P. (1995). Social Information Filtering: Algorithms for Automating 'Word of Mouth'. In Proceedings of CHI '95. Denver, CO.

28
Terveen, L., Hill, W., Amento, B., McDonald, D., and Creter, J. (1997). PHOAKS: A System for Sharing Recommendations. Communications of the ACM, 40(3). pp. 59-62.

29
Ungar, L. H., and Foster, D. P. (1998) Clustering Methods for Collaborative Filtering. In Workshop on Recommender Systems at the 15th National Conference on Artificial Intelligence.



Badrul M. Sarwar
2001-02-19