A user-centric evaluation framework of recommender systems

CEUR Workshop Proceedings

Volumn 612, Issue , 2010, Pages 14-21

  Pu, Pearl ^a   Chen, Li ^b  

^a EPFL   (Switzerland)

^b HONG KONG BAPTIST UNIVERSITY   (Hong Kong)

Author keywords

E commerce recommender; Evaluation of decision support; Post study questionnaire; Quality measurement; Quality of user experience; Recommender systems; Usability evaluation

Indexed keywords

DECISION SUPPORTS; POST-STUDY QUESTIONNAIRE; QUALITY MEASUREMENTS; USABILITY EVALUATION; USER EXPERIENCE;

DECISION SUPPORT SYSTEMS; ELECTRONIC COMMERCE; QUALITY CONTROL; SURVEYS;

RECOMMENDER SYSTEMS;

EID: 84888996027     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (33)

1. Adomavicius, G. and Tuzhilin, A. 2005. Toward the Next Generation of Recommender Systems: A Survey of the Stateof- The-Art and Possible Extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734-749.
2. Beenen, G., Ling, K., Wang, X., Chang, K., Frankowski, D., Resnick, P., et al. 2004. Using social psychology to motivate contributions to online communities. In CSCW '04: Proceedings of the ACM Conference On Computer Supported Cooperative Work. New York: ACM Press.
3. Castagnos, S., Jones, N., and Pu, P. 2009. Recommenders' Influence on Buyers' Decision Process. In proceedings of the 3rd ACM Conference on Recommender Systems (RecSys 2009), 361-364.
4. Chen, L. and Pu, P. 2006. Trust Building with Explanation Interfaces. In Proceedings of International Conference on Intelligent User Interface (IUI'06), 93-100.
5. Chen, L. and Pu, P. 2008. A Cross-Cultural User Evaluation of Product Recommender Interfaces. RecSys 2008, 75-82.
6. Chen, L. and Pu, P. 2009. Interaction Design Guidelines on Critiquing-based Recommender Systems. User Modeling and User-Adapted Interaction Journal (UMUAI), Springer Netherlands, Volume 19, Issue3, 167-206.
7. Davis, F.D. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quart. 13 319-339.
8. Grabner-Kräuter, S. and Kaluscha, E.A. 2003. Empirical research in on-line trust: A review and critical assessment Int. J. Hum.-Comput. Stud. (IJMMS) 58(6), 783-812.
9. Herlocker, J.L., Konstan, J.A., Borchers, A., and Riedl, J. An algorithmic framework for performing collaborative filtering. In Proc. of ACM SIGIR 1999, ACM Press (1999), 230-237.
10. Herlocker, J.L., Konstan, J.A., and Riedl, J. 2000. Explaining collaborative filtering recommendations. CSCW 2000, 241- 250.
11. Herlocker, J.L., Konstan, J.A., Terveen, L.G., and Riedl, J. 2004. Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. 22(1), 5-53.
12. Hu, R. and Pu, P. Potential Acceptance Issues of Personalitybased Recommender Systems. In Proceedings of ACM Conference on Recommender Systems (RecSys'09), New York City, NY, USA, October 22-25, 2009.
13. Jones, N., and Pu, P. 2007. User Technology Adoption Issues in Recommender Systems. In Proceedings of Networking and Electronic Commerce Research Conference (NAEC2007), 379-394.
14. Jones, N., Pu, P., and Chen, L. 2009. How Users Perceive and Appraise Personalized Recommendations. Proceedings of User Modeling, Adaptation, and Personalization conference (UMAP09), 461-466.
15. Kirakowski, J. 1993. SUMI: The Software Usability Measurement Inventory. British Journal of Educational Technology, 24 (3) 210-214.
16. Lewis, J.R. 1993. IBM computer usability satisfaction questionnaires: psychometric evaluation and instructions for use.
17. McGinty, L. and Smyth, B. On the role of diversity in conversational recommender systems. In Proceedings of the Fifth International Conference on Case-Based Reasoning (ICCBR'03), 2003, 276-290.
18. McNee, S.M., Albert, I., Cosley, D., Gopalkrishnan, P., Lam, S.K., Rashid, A.M., Konstan, J.A. and Riedl, J. On the Recommending of Citations for Research Papers. In Proc. of ACM CSCW 2002, ACM Press (2002), 116-125.
19. McNee, S.M., Lam, S.K., Konstan, J.A., Riedal, J. 2003. Interfaces for eliciting new user preferences in recommender systems. User Modeling 2003, 178-187.
20. McNee, S.M., Riedl, J., and Konstan, J.A. 2006. Being accurate is not enough: How accuracy metrics have hurt recommender systems. CHI Extended Abstracts 2006, 1097-1101.
21. Nunnally, J. C. 1978. Psychometric Theory.
22. Ozok, A.A, Fan, Q., Norcio, A.F. 2010. Design guidelines for effective recommender system interfaces based on a usability criteria conceptual model: Results from a college student population. Behaviour & Information Technology, Volume 29, Issue 1, 57 - 83.
23. Pu, P., Chen, L., and Kumar, P. 2008. Evaluating Product Search and Recommender Systems for E-Commerce Environments. Electronic Commerce Research Journal, 8(1- 2), June, 1-27.
24. Pu, P., Zhou, M., and Castagnos, S. 2009. Critiquing Recommenders for Public Taste Products. In proceedings of the 3rd ACM Conference on Recommender Systems (RecSys 2009), 249-252.
25. Sarwar, B., Karypis, G., Konstan, J., and Riedl, J. 2000. Analysis of recommendation algorithms for e-commerce. ACM Conference on Electronic Commerce, 158-167.
26. Sarwar, B., Karypis, G., Konstan, J., and Riedl, J. 2001. Item-based collaborative filtering recommendation algorithms. WWW, 285-295.
27. Simonson, I. 2005. Determinants of customers' responses to customized offers: Conceptual framework and research propositions. Journal of Marketing, 69 (January 2005), 32-45.
28. Sinha, R. and Swearingen, K. 2001. Comparing Recommendations made by Online Systems and Friends. Proceedings of the DELOS-NSF Workshop on Personalization and Recommender Systems in Digital Libraries, 2001.
29. Stohr, E.A. and Viswanathan, S. 1999. Recommendation systems: Decision support for the information economy. Emerging Information Technologies, K. E. Kendall, Ed. Thousand Oaks, CA: SAGE, 1999, 21-44.
30. Swearingen, K. and Sinha, R. 2002. Interaction design for recommender systems. In Interactive Systems (DIS2002).
31. Tintarev, N. and Masthoff, J. 2007. Survey of explanations in recommender systems. ICDE Workshops 2007, 801-810.
32. Venkatesh, V., Morris, M.G., Davis, G.B. and Davis, F.D. 2003. User acceptance of information technology: Toward a unified view. MIS Quarterly 2003, 27, 3, 425-478.
33. Ziegler, C.N., McNee, S.M., Konstan, J.A., and Lausen, G., Improving Recommendation Lists through Topic Diversification. In Proc. of WWW 2005, ACM Press (2005), 22-32.