A taxonomy for generating explanations in recommender systems

AI Magazine

Volumn 32, Issue 3, 2011, Pages 90-98

  Friedrich, Gerhard ^a   Zanker, Markus ^a  

^a UNIVERSITY OF KLAGENFURT   (Austria)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION MAKING; RECOMMENDER SYSTEMS;

RESEARCH ISSUES;

TAXONOMIES;

EID: 84255191513     PISSN: 07384602     EISSN: None     Source Type: Journal    
DOI: 10.1609/aimag.v32i3.2365     Document Type: Article

References (28)

1. Adomavicius, G., and Tuzhilin, A. 2005. Toward 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(6):734-749. (Pubitemid 40860454)
2. Bilgic, M., and Mooney, R. J. 2005. Explaining Recommendations: Satisfaction Versus Promotion. Paper presented at Beyond Personalization 2005: A Workshop on the Next Stage of Recommender Systems Research, San Diego, CA, 9-12 Jan.
3. Brewer, W. F.; Chinn, C. A.; and Samarapungavan, A. 1998. Explanation in Scientists and Children. Minds and Machines 8(1):119-136. (Pubitemid 128513024)
4. Buchanan, B., and Shortliffe, E. 1984. Rule Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project. Reading, MA: Addison-Wesley.
5. Chandrasekara, B. 1991. Models Versus Rules, Deep Versus Compiled Content Versus Form: Some Distinctions in Knowledge Systems Research. IEEE Expert 6(2):75-79.
6. Chesñevar, C. I.; Maguitman, A. G.; and Loui, R. P. 2000. Logical Models of Argument. ACM Computing Surveys 32(4):337-383.
7. Eiter, T.; Gottlob, G.; and Leone, N. 1997. Abduction from Logic Programs: Semantics and Complexity. Theoretical Computer Science 189(1-2):129-177. (Pubitemid 127451560)
8. Felfernig, A.; Friedrich, G.; Schubert, M.; Mandl, M.; Mairitsch, M.; and Teppan, E. 2009. Plausible Repairs for Inconsistent Requirements. In Proceedings of the 21st International Joint Conference on Artificial Intelligence, 791-796. Menlo Park, CA: AAAI Press.
9. Felfernig, A.; Friedrich, G.; Teppan, E.; and Isak, K. 2008. Intelligent Debugging and Repair of Utility Constraint Sets in Knowledge-Based Recommender Applications. In Proceedings of the 13th ACM International Conference on Intelligent User Interfaces, 218-226. New York: Association for Computing Machinery.
10. Friedrich, G. 2004. Elimination of Spurious Explanations. In Proceedings of the 16th European Conference on Artificial Intelligence, ed. R. L. de Mantaras and L. Saitta, 813-817. Amsterdam, The Netherlands: IOS Press.
11. Gönül, M. S.; Önkal-Atay, D.; and Lawrence, M. 2006. The Effects of Structural Characteristics of Explanations on Use of a DSS. Decision Support Systems 42(3):1481-1493. (Pubitemid 44648437)
12. Herlocker, J. L.; Konstan, J. A.; and Riedl, J. 2000. Explaining Collaborative Filtering Recommendations. In Proceedings of the 2000 ACM Conference on Computer Supported Cooperative Work, 241-250. New York: Association for Computing Machinery. (Pubitemid 32400055)
13. Jannach, D. 2004. Advisor Suite-A Knowledge-Based Sales Advisory System. In Proceedings of the 16th European Conference on Artificial Intelligence, ed. R. L. de Mantaras and L. Saitta, 720-724. Amsterdam, The Netherlands: IOS Press.
14. Jannach, D.; Zanker, M.; Felfernig, A.; and Friedrich, G. 2010. Recommender Systems: An Introduction. New York: Cambridge University Press.
15. Koren, Y.; Bell, R. M.; and Volinsky, C. 2009. Matrix Factorization Techniques for Recommender Systems. IEEE Computer 42(8):30-37.
16. Mahmood, T.; Ricci, F.; and Venturini, A. 2009. Improving Recommendation Effectiveness: Adapting a Dialogue Strategy in Online Travel Planning. International Journal of Information Technology and Tourism 11(4):285-302.
17. Pu, P., and Chen, L. 2007. Trust-Inspiring Explanation Interfaces for Recommender Systems. Knowledge-Based Systems 20(6):542-556. (Pubitemid 47068958)
18. Ricci, F.; Rokach, L.; Shapira, B.; and Kantor, P. B., eds. 2011. Recommender Systems Handbook. Berlin: Springer.
19. Sqalli, M. H., and Freuder, E. C. 1996. Inference-Based Constraint Satisfaction Supports Explanation. In Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 318-325. Menlo Park, CA: AAAI Press.
20. Symeonidis, P.; Nanopoulos, A.; and Manolopoulos, Y. 2008. Providing Justifications in Recommender Systems. IEEE Transactions on Systems, Man, and Cybernetics, Part A 38(6):1-1272.
21. Teppan, E. C., and Felfernig, A. 2009. Asymmetric Dominance-and Compromise Effects in the Financial Services Domain. In Proceedings of the 2009 IEEE Conference on Commerce and Enterprise Computing, ed. B. Hofreiter and H. Werthner, 57-64. Los Alamitos, CA: IEEE Computer Society.
22. Tintarev, N., and Masthoff, J. 2011. Designing and Evaluating Explanations for Recommender Systems. In Recommender Systems Handbook, ed. F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, 479-510. Berlin: Springer.
23. Tversky, A., and Kahneman, D. 1981. The Framing of Decisions and the Psychology of Choice. Science 211(4481):453-458. (Pubitemid 11145313)
24. Vig, J.; Sen, S.; and Riedl, J. 2009. Tagsplanations: Explaining Recommendations Using Tags. In Proceedings of the 14th International Conference on Intelligent User Interfaces, 47-56. New York: Association for Computing Machinery.
25. Ye, L. R., and Johnson, P. E. 1995. The Impact of Explanation Facilities in User Acceptance of Expert System Advice. MIS Quarterly 19(2):157-172.
26. Yoo, K. H., and Gretzel, U. 2011. Creating More Credible and Persuasive Recommender Systems: The Influence of Source Characteristics on Recommender System Evaluations. In Recommender Systems Handbook, ed. F. Ricci, L. Rokach, B. Shapira, and P. B. Kantor, 455-477. Berlin: Springer.
27. Zanker, M., and Ninaus, D. 2010. Knowledgeable Explanations for Recommender Systems. In Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence (WI), 657-660. Piscataway, NJ: Institute of Electrical and Electronics Engineers.
28. Zanker, M.; Jessenitschnig, M.; and Schmid, W. 2010. Preference Reasoning with Soft Constraints in Constraint-Based Recommender Systems. Constraints 15(4):574-595.