Implicit feedback recommendation via implicit-to-explicit ordinal logistic regression mapping

CEUR Workshop Proceedings

Volumn 791, Issue , 2011, Pages

  Parra, Denis ^a   Karatzoglou, Alexandros ^b   Amatriain, Xavier ^b   Yavuz, Idil ^a  

^a UNIVERSITY OF PITTSBURGH   (United States)

^b Telefonica Research   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EXPLICIT FEEDBACK; IMPLICIT FEEDBACK; LOGISTIC REGRESSION MODELING; MUSIC RECOMMENDATION; ORDINAL LOGISTIC REGRESSION; PERSONAL INFORMATION; RECOMMENDATION ALGORITHMS; RECOMMENDATION METHODS;

ALGORITHMS; COHERENT SCATTERING; RECOMMENDER SYSTEMS; REGRESSION ANALYSIS;

FEEDBACK;

EID: 84891945520     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. Y. Hu, Y. Koren, and C. Volinsky. Collaborative filtering for implicit feedback datasets. In Proceedings of ICDM 2008, 2008.
2. F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, editors. Recommender Systems Handbook. Springer, 2011.
3. Douglas Oard and Jinmook Kim. Implicit feedback for recommender systems. In in Proceedings of the AAAI Workshop on Recommender Systems, pages 81{83, 1998.
4. G. Potter. Putting the collaborator back into collaborative filtering. In 2nd KDD Workshop on Large-Scale Recommender Systems and the Netix Prize Competition, 2008.
5. D. M. Nichols. Implicit rating and filtering. In In Proceedings of the Fifth DELOS Workshop on Filtering and Collaborative Filtering, pages 31{36, 1997.
6. X. Amatriain, J.M. Pujol, and N. Oliver. I like it... i like it not: Evaluating user ratings noise in recommender systems. In Proc. of the 2009 Conference on User Modeling, Adaptation, and Personalization, 2009.
7. G. Jawaheer, M. Szomszor, and P. Kostkova. Characterisation of explicit feedback in an online music recommendation service. In Proceedings of the fourth ACM conference on Recommender systems, RecSys '10, pages 317{320, 2010.
8. D. Parra and X. Amatriain. Walk the talk: Analyzing the relation between implicit and explicit feedback for preference elicitation. In Proc. of the 2011 Conference on User Modeling, Adaptation, and Personalization, 2011.
9. M. Morita and Y. Shinoda. Information filtering based on user behavior analysis and best match text retrieval. In SIGIR '94: Proceedings of the 17th annual international ACM SIGIR conference, pages 272{281, New York, NY, USA, 1994. Springer-Verlag New York, Inc.
10. Joseph A. Konstan, Bradley N. Miller, David Maltz, Jonathan L. Herlocker, Lee R. Gordon, and John Riedl. Grouplens: Applying collaborative filtering to usenet news. Commun. ACM, 40(3):77{87, 1997. (Pubitemid 127441134)
11. D. Oard and J. Kim. Modeling information content using observable behavior. In Proc. of the ASIST Annual Meeting, pages p481{88, 2001.
12. N.S. Koh, N. Hu, and E. K. Clemons. Do online reviews reect a product's true perceived quality? - An investigation of online movie reviews across cultures. Electronic Commerce Research and Applications, 2010.
13. T. Lee, Y. Park, and Y. Park. A time-based approach to e-ective recommender systems using implicit feedback. Expert Syst. Appl., 34(4):3055{3062, 2008. (Pubitemid 351173808)
14. Gawesh Jawaheer, Martin Szomszor, and Patty Kostkova. Comparison of implicit and explicit feedback from an online music recommendation service. In Proceedings of the 1st International Workshop on Information Heterogeneity and Fusion in Recommender Systems, 2010.
15. S. Kordumova, I. Kostadinovska, M. Barbieri, V. Pronk, and J. Korst. Personalized implicit learning in a music recommender system. In UMAP 2010, 2010.
16. Gediminas Adomavicius and Alexander Tuzhilin. Context-aware recommender systems. In Francesco Ricci, Lior Rokach, Bracha Shapira, and Paul B. Kantor, editors, Recommender Systems Handbook, pages 217{253. Springer US, 2011.
17. J. Neter, M. H. Kutner, C. J. Nachtsheim, and W. Wasserman. Applied Linear Statistical Models. Irwin, Chicago, 1996.
18. Jonathan L. Herlocker, Joseph A. Konstan, Loren G. Terveen, and John T. Riedl. Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst., 22(1):5{53, 2004.
19. Christopher D. Manning, Prabhakar Raghavan, and Hinrich Schtze. Introduction to Information Retrieval. Cambridge University Press, New York, NY, USA, 2008.
20. Kalervo Järvelin and Jaana Kekäläinen. Cumulated gain-based evaluation of ir techniques. ACM Trans. Inf. Syst., 20:422{446, October 2002. (Pubitemid 44642296)