Social factors in group recommender systems

ACM Transactions on Intelligent Systems and Technology

Volumn 4, Issue 1, 2013, Pages

  Quijano Sanchez, Lara ^a   Recio Garcia, Juan A ^a   Diaz Agudo, Belen ^a   Jimenez Diaz, Guillermo ^a  

^a UNIVERSIDAD COMPLUTENSE DE MADRID   (Spain)

Author keywords

Memory; Personality; Recommender systems; Social networks; Trust

Indexed keywords

DECISION MAKING PROCESS; GROUP MEMBERS; GROUP RECOMMENDER SYSTEMS; GROUP RECOMMENDERS; INDIVIDUAL BEHAVIOR; LONG-TERM RECOMMENDATIONS; PERSONALITY; SOCIAL FACTOR; SOCIAL NETWORKS; TRUST;

DATA STORAGE EQUIPMENT;

RECOMMENDER SYSTEMS;

EID: 84873643151     PISSN: 21576904     EISSN: 21576912     Source Type: Journal    
DOI: 10.1145/2414425.2414433     Document Type: Article

References (41)

1. AAMODT, A. AND PLAZA, E. 1994. Case-based reasoning: Foundational issues, methodological variants, and system approaches. Artif. Intell. Commun. 7, 1, 39-59.
2. AMER-YAHIA, S., ROY, S. B., CHAWLAT, A., DAS, G., AND YU, C. 2009. Group recommendation: semantics and efficiency. Proc. VLDB Endow. 2, 1, 754-765.
3. ARDISSONO, L., GOY, A., PETRONE, G., SEGNAN, M., AND TORASSO, P. 2003. Intrigue: Personalized recommendation of tourist attractions for desktop and handset devices. Appl. Artif. Intell. 17, 8, 687-714.
4. BACCIGALUPO, C. AND PLAZA, E. 2007. A case-based song scheduler for group customised radio. In Proceedings of the 7th International Conference on Case-Based Reasoning (ICCBR '07). R. Weber and M. M. Richter, Eds., Lecture Notes in Computer Science, vol. 4626, Springer, 433-448.
5. BALTRUNAS, L., MAKCINSKAS, T., AND RICCI, F. 2010. Group recommendations with rank aggregation and collaborative filtering. In Proceedings of the 4th ACM Conference on Recommender Systems (RecSys '10). ACM, New York, NY, 119-126.
6. BARSADE, S. G. 2002. The ripple effect: Emotional contagion and its influence on group behavior. Admin. Sci. Quart. 47, 4, 644-675.
7. BERKOVSKY, S. AND FREYNE, J. 2010. Group-based recipe recommendations: analysis of data aggregation strategies. In Proceedings of the 4th ACM Conference on Recommender Systems (RecSys '10). ACM, New York, NY, 111-118.
8. BOBADILLA, J., SERRADILLA, F., AND HERNANDO, A. 2009. Collaborative filtering adapted to recommender systems of e-learning. Knowl.-Based Syst. 22, 4, 261-265.
9. CHEN, Y.-L., CHENG, L.-C., AND CHUANG, C.-N. 2008. A group recommendation system with consideration of interactions among group members. Expert Syst. Appl. 34, 3, 2082-2090.
10. COOPER, W. S. 1968. Expected search length: A single measure of retrieval effectiveness based on the weak ordering action of retrieval systems. Amer. Document. 19, 1, 30-41.
11. CROSSEN, A., BUDZIK, J., AND HAMMOND, K. J. 2002. Flytrap: intelligent group music recommendation. In Proceedings of the 7th International Conference on Intelligent User Interfaces (IUI '02). ACM, 184-185.
12. DEUTSCH, M. AND GERARD, H. B. 1955. A study of normative and informational social influences upon individual judgement. J. Abnormal Social Psych. 51, 3, 629-36.
13. GILBERT, E. AND KARAHALIOS, K. 2009. Predicting tie strength with social media. In Proceedings of the 27th International Conference on Human Factors in Computing Systems (CHI '09). ACM, 211-220.
14. GOLBECK, J. 2006a. Combining provenance with trust in social networks for semantic web content filtering. In Provenance and Annotation of Data, International Provenance and Annotation Workshop, Revised Selected Papers, L. Moreau and I. T. Foster, Eds., Lecture Notes in Computer Science, vol. 4145, Springer, 101-108.
15. GOLBECK, J. 2006b. Generating predictive movie recommendations from trust in social networks. In Proceedings of the 4th International Conference on Trust Management. 93-104.
16. GRANOVETTER, M. 1973. The strength of weak ties. Amer. J. Sociology 78, 6, 1360-1380.
17. HATFIELD, E., CACIOPPO, J., AND RAPSON, R. 1994. Emotional Contagion. Studies in Emotion and Social Interaction. Cambridge University Press.
18. HERLOCKER, J. L., KONSTAN, J. A., TERVEEN, L. G., AND RIEDL, J. T. 2004. Evaluating collaborative filtering recommender systems. ACM Trans. Inf. Syst. 22, 1, 5-53.
19. JAMESON, A. 2004. More than the sum of its members: challenges for group recommender systems. In Proceedings of the Working Conference on Advanced visual interfaces (AVI '04). ACM, 48-54.
20. JAMESON, A. AND SMYTH, B. 2007. Recommendation to groups. In The Adaptive Web, Methods and Strategies of Web Personalization, P. Brusilovsky, A. Kobsa, and W. Nejdl, Eds., Lecture Notes in Computer Science, vol. 4321, Springer, 596-627.
21. KELLEHER, J. AND BRIDGE, D. G. 2004. An accurate and scalable collaborative recommender. Artif. Intell. Rev. 21, 3-4, 193-213.
22. KIM, J. K., KIM, H. K., OH, H. Y., AND RYU, Y. U. 2010. A group recommendation system for online communities. Int. J. Inf. Manage. 30, 3, 212-219.
23. LEVIN, D. Z., CROSS, R., AND ABRAMS, L. C. 2004. The strength of weak ties you can trust: the mediating role of trust in effective knowledge transfer. Manage. Sci. 50, 1477-1490.
24. LIEBERMAN, H., DYKE, N. W. V., AND VIVACQUA, A. S. 1999. Let's browse: A collaborative web browsing agent. In Proceedings of the International Conference on Intelligent User Interfaces. 65-68.
25. LINDEN, G., SMITH, B., AND YORK, J. 2003. Amazon.com recommendations: Item-to-item collaborative filtering. IEEE Internet Comput. 7, 76-80.
26. MASTHOFF, J. 2004. Group modeling: Selecting a sequence of television items to suit a group of viewers. User Model. User-Adapt. Interact. 14, 1, 37-85.
27. MASTHOFF, J. AND GATT, A. 2006. In pursuit of satisfaction and the prevention of embarrassment: affective state in group recommender systems. User Model. User-Adapt. Interact. 16, 3-4, 281-319.
28. MCCARTHY, J. F. 2002. Pocket restaurant finder: A situated recommender systems for groups. In Proceedings of Workshop on Mobile Ad-Hoc Communication at the ACM Conference on Human Factors in Computer Systems.
29. MCCARTHY, J. F. AND ANAGNOST, T. D. 1998. MusicFX: An arbiter of group preferences for computer aupported collaborative workouts. In Proceedings of the ACM Conference on Computer Supported Cooperative Work (CSCW '98). ACM, 363-372.
30. MCCARTHY, K., MCGINTY, L., SMYTH, B., AND SALAMÓ, M. 2006. The needs of the many: A case-based group recommender system. Adv. Case-Based Reas. 4106, 196-210.
31. O'CONNOR, M., COSLEY, D., KONSTAN, J. A., AND RIEDL, J. 2001. Polylens: a recommender system for groups of users. In Proceedings of the European Conference on Computer Supported Cooperative Work (ECSCW'01). Kluwer Academic Publishers, Norwell, MA, 199-218.
32. O'DONOVAN, J. AND SMYTH, B. 2005. Trust in recommender systems. In Proceedings of the 10th International Conference on Intelligent User Interfaces (IUI '05). ACM, 167-174.
33. RECIO-GARCÍA, J. A., DÍAZ-AGUDO, B., AND GONZÁLEZ-CALERO, P. A. 2008. Prototyping Recommender Systems in jCOLIBRI. In Proceedings of the ACM Conference on Recommender syStems (RecSys '08). ACM, New York, NY, 243-250.
34. RECIO-GARCÍA, J. A., JIMENEZ-DIAZ, G., SÁNCHEZ-RUIZ, A. A., AND DÍAZ-AGUDO, B. 2009. Personality aware recommendations to groups. In Proceedings of the ACM Conference on Recommender Systems. L. D. Bergman, A. Tuzhilin, R. D. Burke, A. Felfernig, and L. Schmidt-Thieme, Eds., ACM, 325-328.
35. SARWAR, B., KARYPIS, G., KONSTAN, J., AND REIDL, J. 2001. Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th International Conference on World Wide Web (WWW '01). ACM, New York, NY, 285-295.
36. SCHAFER, J., FRANKOWSKI, D., HERLOCKER, J., AND SEN, S. 2007. Collaborative filtering recommender systems. In The Adaptive Web, Lecture Notes in Computer Science, vol. 4321, Springer, 291-324.
37. SINHA, R. R. AND SWEARINGEN, K. 2001. Comparing recommendations made by online systems and friends. In Proceedings of the DELOS Workshop: Personalisation and Recommender Systems in Digital Libraries.
38. THOMAS, K. AND KILMANN, R. 1974. Thomas-Kilmann Conflict Mode Instrument. Tuxedo, NY.
39. VICTOR, P., CORNELIS, C., COCK, M. D., AND TEREDESAI, A. 2008. Key figure impact in trust-enhanced recom-mender systems. AI Com. 21, 2-3, 127-143.
40. WU, A., DIMICCO, J. M., AND MILLEN, D. R. 2010. Detecting professional versus personal closeness using an enterprise social network site. In Proceedings of the 28th International Conference on Human Factors in Computing Systems (CHI '10). ACM, New York, NY, 1955-1964.
41. YU, Z., ZHOU, X., HAO, Y., AND GU, J. 2006. TV program recommendation for multiple viewers based on user profile merging. User Model. User-Adapt. Interact. 16, 1, 63-82.