The effects of transparency on perceived and actual competence of a content-based recommender

CEUR Workshop Proceedings

Volumn 543, Issue , 2009, Pages

  Cramer, Henriette ^a   Wielinga, Bob ^a   Ramlal, Satyan ^a   Evers, Vanessa ^a   Rutledge, Lloyd ^c,d   Stash, Natalia ^b  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

^c TELEMATICA INSTITUUT   (Netherlands)

^d CWI   (Netherlands)

Author keywords

Actual competence; Explanations; Perceived competence; Recommender systems; Transparency

Indexed keywords

ACTUAL COMPETENCE; CONTENT-BASED; EXPLANATIONS; PERCEIVED COMPETENCE; USERS' PERCEPTION; WEB RECOMMENDER SYSTEMS;

RECOMMENDER SYSTEMS; WEBSITES;

TRANSPARENCY;

EID: 84882657816     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (35)

1. Amazon, www.amazon.com/gp/yourstore/
2. Aroyo, L., Stash, N., Wang, Y., Gorgels, P. and Rutledge, L. CHIP Demonstrator: Semantics-driven Recommendations and Museum Tour Generation. In Proc. ISWC 2007, Springer (2007), 879-886.
3. Bedi, P., Kaur, H. and Marwaha, S. Trust Based Recommender System for Semantic Web. In Proc. IJCAI 2007, (2007), 2677-2682.
4. Bilgic, M. and Mooney, R.J. Explaining Recommendations: Satisfaction vs. Promotion, In Proc. Beyond Personalization Workshop at IUI 2005, (2005).
5. Celma, O. Foafing the Music: Bridging the semantic gap in music recommendation, In Proc. ISCW 2006, (2006).
6. Cheverst, K., Byun, H.E., Fitton, D., Sas, C., Kray, C. and Villar, N. Exploring Issues of User Model Transparency and Proactive Behaviour in an Office Environment Control System. User modeling and User-adapted interaction 15, 3-4 (2005), 235-273.
7. Cramer, H., Ramlal, S., Evers, V., Van Someren, M. Wielinga, B., Rutledge, L., Aroyo, L. and Stash, N. User interaction with a content-based art recommender. The effects of transparency on trust and acceptance, accepted for publication.
8. Dzindolet, M. The role of trust in automation reliance, Int. J. of Human-Computer Studies 58, 6 (2003), 697-718.
9. Golbeck, J. Semantic Web Interaction through Trust Network Recommender Systems. In Proc. ISWC 2005.
10. Herlocker, J.L., Konstan, J.A., Terveen, L.G., and Riedl, J.T. Evaluating Collaborative Filtering Recommender Systems. ACM TOIS 22, 1 (2004), 5-53.
11. Herlocker, J.L., Konstan, J.A. and Riedl, J.T. Explaining collaborative filtering recommendations, In Proc CSCW 2000, ACM Press (2000), 241-250.
12. Höök, K., Karlgren, J., Waern, A., Dahlbeck, N., Jansson, C. G., Karlgren, K., and Lemaire, B. A Glass Box Approach to Adaptive Hypermedia., User Modeling and User-Adapted Interaction 6, 2-3 (1996), 157-184.
13. Hyvönen, E., Mäkelä, E., Salminen, M., Valo, A., Viljanen, K., Saarela, S., Junnila, M., and Kettula, S. MuseumFinland - Finnish Museums on the Semantic Web. J. of Web Semantics 3, 2 (2005), 224-241.
14. Jøsang, A. and Lo Presti, S. Analysing the Relationship between Risk and Trust. International Conference on Trust Management, Springer (2004), 135-145.
15. Kay, J. Scrutable adaptation: because we can and must. In Proc. AH 2006, Springer (2006), 11-19.
16. Kurasaki, K. S. Intercoder Reliability for Validating Conclusions Drawn from Open-Ended Interview Data. Field Methods 12, 3 (2000), 179-194.
17. Lee J.D. and See K.A. Trust in automation: designing for Appropriate Reliance. Human Factors 42, 1 (2004), 50-80.
18. Loizou, A. and Dasmahapatra, S. Recommender Systems for the Semantic Web. In Proc. ECAI 2006 Recommender Systems Workshop (2006).
19. McGuinness, D.L., Ding, L., Glass, A., Chang, C., Zeng, H. and Furtado, V. Explanation Interfaces for the Semantic Web: Issues and Models, In Proc. SWUI 2006, (2006).
20. McNee, S.M., Riedl, J. and Konstan, J. Accurate is not always good: How Accuracy Metrics have hurt Recommender Systems. Ext. Abstracts CHI 2006, ACM Press (2006), 1-5.
21. McSherry, D. Explanation in Recommender Systems. Artificial Intelligence Review 24, 2 (2005), 179-197.
22. Movielens, www.movielens.org
23. Nejdl, W., Ghita, S., Paiu R. Semantically Rich Recommendations in Social Networks for Sharing, Exchanging and Ranking Semantic Context. In Proc. ISWC 2005, (2005).
24. Pu, P. and Chen, L. Trust-Inspiring Explanation Interfaces for Recommender Systems. Knowledge-Based Systems Journal 20, 6 (2007), 542-556.
25. Revyu, www.revyu.com
26. Schreiber, G., Amin, A., van Assem, M., de Boer, V., Hardman, L., Hildebrand, M., Hollink, L., Huang, Z., van Kersen, J., de Niet, M., Omelayenko, B., van Ossenbruggen, J., Siebes, R., Taekema, J., Wielemaker, J., and Wielinga, B. J. Multimedian e-culture demonstrator. In Proc. International Semantic Web Conference, (2006), 951-958.
27. Semantic Web Challenge 2007, challenge.semanticweb.org.
28. Sinclair, P., Lewis, P., Martinez, K., Addis, M., and Prideaux, D. Semantic web integration of 33 cultural heritage sources. In Proc. World WideWeb, (2006), 1047-1048.
29. Sinha, R., Swearingen, K. The Role of Transparency in Recommender Systems. In Ext. Abstracts CHI 2002, ACM Press (2002) 830-831.
30. Tintarev, N. and Masthoff, J. Effective explanations of recommendations: user-centered design, In Proc. RecSys 2007, ACM Press (2007), 153-156.
31. Venkatesh, V., Morris, M.G., Davis, G.B., and Davis, F.D. User Acceptance of Information Technology: Toward a Unified View, MIS Quarterly 27, 3 (2003), 425-478.
32. Waern, A. User Involvement in Automatic Filtering: An Experimental Study. User Modeling and User-Adapted Interaction 14, 2-3 (2004), 201-237.
33. Wang, W. and Benbasat, I. Recommendation Agents for Electronic Commerce: Effects of Explanation Facilities on Trusting Beliefs. Journal of Management Information Systems 23, 4 (2007), 217-246.
34. Ziegler, C-N. Semantic Web Recommender Systems, In Selected and Revised Papers EDBT 2004, (2004), 78-89.
35. Ziegler, C-N., Lausen, G. and Schmidt-Thieme, L. Taxonomy-driven Computation of Product Recommendations, In Proc. CIKM 2004, ACM Press (2004), 406 - 415.