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Resources on Collaborative Filtering

Press

The Science of the Sleeper How the Information Age could blow away the blockbuster. Malcolm Gladwell on Collaborative Filtering.

References

  1. Herlocker, J., Konstan, J., and Riedl, J., Explaining Collaborative Filtering Recommendations. Proceedings of the ACM 2000 Conference on Computer Supported Cooperative Work , December 2-6, 2000.
  2. Herlocker, J., Konstan, J., Borchers, A., Riedl, J.. An Algorithmic Framework for Performing Collaborative Filtering. Proceedings of the 1999 Conference on Research and Development in Information Retrieval. Aug. 1999
  3. Badrul Sarwar, George Karypis, Joseph Konstan, and John Riedl Item-based Collaborative Filtering Recommendation Algorithms . WWW10, May 1-5, 2001, Hong Kong.
  4. Eigentaste: A Constant Time Collaborative Filtering Algorithm , Ken Goldberg, Theresa Roeder, Dhruv Gupta, and Chris Perkins, UCB ERL Technical Report M00/41. August 20000.
  5. Empirical Analysis of Predictive Algorithms for Collaborative Filtering Jack Breese, David Heckerman, Carl Kadie Microsoft Research.
  6. Automated Collaborative Filtering and Semantic Transports by Alexander Chislenko
  7. Analysis of the Axiomatic Foundations of Collaborative Filtering by David M. Pennock, Eric Horvitz
  8. Web-Collaborative Filtering: Recommending Music by Crawling The WebWilliam W. Cohen, Wei Fan
  9. "Which Intelligent Agents Are Smarter? An Analysis of Relative Performance of Collaborative and Individual Based Recommendation Agents" Dan Ariely and Manuel Aparicio IV, John G. Lynch, Jr..
  10. GroupLens: An Open Architecture for Collaborative Filtering of Netnews
  11. Augmenting Information Seeking on the World Wide Web Using Collaborative Filtering Techniquesby Don Turnbull
  12. Interacting with Recommender Systems , Don Turnbull CHI'99
  13. Shardanand U. and Maes (1995), Social information filtering: Algorithms for automating "word of mouth", Proceedings of CHI'95 -- Human Factors in Computing Systems, 210-217
  14. Recommending and Evaluating Choices in a Virtual Community of Use Will Hill, Larry Stead, Mark Rosenstein, George Furnas, Bellcore CHI'95
  15. Pointing the Way: Active Collaborative Filtering David Maltz, Carnegie Mellon University; Kate Ehrlich, Lotus Development Corporation CHI'95
  16. Implicit Rating and Filtering In Proceedings of the 5th DELOS Workshop on Filtering and Collaborative Filtering, Budapest, Hungary, 10-12 November 1997, ERCIM, 31-36. ISBN: 2-912335-04-3.
  17. Using Memex to archive and mine community Web browsing experience. Chakrabarti et. al., WWW9
  18. Trawling the web for emerging cyber-communities Kumar et. al., IBM Almaden.
  19. An Analysis of Prediction Algorithms for Collaborative Filtering by Bradley N. Miller, John T. Riedl, Joseph A. Konstan U of Mn CS Technical Report TR number: TR 96-035
  20. Collaborative Filtering by Personality Diagnosis: A Hybrid Memory- and Model-Based Approach David M. Pennock, Eric Horvitz Microsoft Research.
  21. Augmenting Information Seeking on the World Wide Web Using Collaborative Filtering Techniques Don Turnbull
  22. Distributing Information for Collaborative Filtering on Usenet Net News David A. Maltz
  23. Agent Based Personalized Information Retrieval - Joshua David Kramer (1997)
  24. ReferralWeb: Combining Social Networks and Collaborative Filtering - Henry Kautz (1997)
  25. An Efficient Boosting Algorithm for Combining Preferences - Yoav Freund, Raj Iyer, Robert.. (1998)
  26. Considering Collaborative Filtering as Groupware: Experiences and Lessons Learned Proceedings of the Second International Conference on Practical Aspects of Knowledge Management
  27. Improving Collaborative Filtering with Multimedia Indexing Techniques to create User-Adapting Web Sites Arnd Kohrs - Bernard Merialdo
  28. Arnd Kohrs and Bernard Merialdo. Clustering for collaborative filtering applications. In Proceedings of CIMCA'99. IOS Press, 1999.
  29. Ungar, L. and D.P. Foster (1998). A formal statistical approach to collaborative filtering. Conference on Automated Learning and Discovery (CONALD).
  30. Latent Class Models for Collaborative Filtering Thomas Hofmann and Jan Puzicha Proceedings of the International Joint Conference in Artificial Intelligence, 1999
  31. Social Information Filtering: Algorithms for Automating "Word of Mouth" Upendra Shardanand and Pattie Maes, CHI '95.
  32. Yezdi Lashkari Feature-Guided Automated Collaborative Filtering

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Patents:

  • John B. Hey (Patent numbers 4870579 and 4996642).

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© 2000-2007 Paul Perry