메뉴 건너뛰기




Volumn 34, Issue 3, 2008, Pages 2082-2090

A group recommendation system with consideration of interactions among group members

Author keywords

Collaborative filtering; Genetic algorithm; Group recommender system

Indexed keywords

ELECTRONIC COMMERCE; GENETIC ALGORITHMS; HUMAN COMPUTER INTERACTION;

EID: 37349129771     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.02.008     Document Type: Article
Times cited : (158)

References (26)
  • 1
    • 20844435854 scopus 로고    scopus 로고
    • Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions
    • Adomavicius G., and Tuzhilin A. 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 (2005) 734-749
    • (2005) IEEE Transactions on Knowledge and Data Engineering , vol.17 , Issue.6 , pp. 734-749
    • Adomavicius, G.1    Tuzhilin, A.2
  • 2
    • 0242498568 scopus 로고    scopus 로고
    • INTRIGUE: Personalized recommendation of tourist attractions for desktop and hand held devices
    • Ardissono L., Goy A., Petrone G., Segnan M., and Torasso P. INTRIGUE: Personalized recommendation of tourist attractions for desktop and hand held devices. Applied Artificial Intelligence 17 8-9 (2003) 687-714
    • (2003) Applied Artificial Intelligence , vol.17 , Issue.8-9 , pp. 687-714
    • Ardissono, L.1    Goy, A.2    Petrone, G.3    Segnan, M.4    Torasso, P.5
  • 3
    • 37349120842 scopus 로고    scopus 로고
    • Armstrong, R., Freitag, D., Joachims, T., & Mitchell, T. (1995). Webwatcher: A learning apprentice for the world wide web. AAAI Spring Symposium on Information Gathering, 6-12.
  • 5
    • 0031103679 scopus 로고    scopus 로고
    • Fab: Content-based, collaborative recommendation
    • Balabanovic M., and Shoham Y. Fab: Content-based, collaborative recommendation. Communications of the ACM 40 3 (1997) 66-72
    • (1997) Communications of the ACM , vol.40 , Issue.3 , pp. 66-72
    • Balabanovic, M.1    Shoham, Y.2
  • 6
    • 37349102831 scopus 로고    scopus 로고
    • Breese, J. S., Heckerman, D., & Kadie, C. (1998). Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the 14th conference on uncertainty in artificial intelligence (pp. 43-52), Madison.
  • 7
    • 0036468125 scopus 로고    scopus 로고
    • A case-based customer classification approach for direct marketing
    • Chiu C. A case-based customer classification approach for direct marketing. Expert Systems with Applications 22 2 (2002) 163-168
    • (2002) Expert Systems with Applications , vol.22 , Issue.2 , pp. 163-168
    • Chiu, C.1
  • 8
    • 0036776464 scopus 로고    scopus 로고
    • A personalized recommender system based on web usage mining and decision tree induction
    • Cho Y.H., Kim J.K., and Kim S.H. A personalized recommender system based on web usage mining and decision tree induction. Expert Systems with Applications 23 3 (2002) 329-342
    • (2002) Expert Systems with Applications , vol.23 , Issue.3 , pp. 329-342
    • Cho, Y.H.1    Kim, J.K.2    Kim, S.H.3
  • 9
    • 84976668719 scopus 로고
    • Using collaborative filtering to weave an information tapestry
    • Goldberg D., Nichols D., Oki B.M., and Terry D. Using collaborative filtering to weave an information tapestry. Communications of the ACM 35 12 (1992) 61-70
    • (1992) Communications of the ACM , vol.35 , Issue.12 , pp. 61-70
    • Goldberg, D.1    Nichols, D.2    Oki, B.M.3    Terry, D.4
  • 11
    • 85015559680 scopus 로고    scopus 로고
    • Herlocker, J. L., Konstan, J. A., Borchers, A., & Riedl, J. (1999). An algorithmic framework for performing collaborative filtering. In Proceedings of the 1999 conference on research and development in information retrieval (pp. 230-237).
  • 12
    • 3042742744 scopus 로고    scopus 로고
    • Latent semantic models for collaborative filtering
    • Hofmann T. Latent semantic models for collaborative filtering. ACM Transactions on Information Systems 22 1 (2004) 89-115
    • (2004) ACM Transactions on Information Systems , vol.22 , Issue.1 , pp. 89-115
    • Hofmann, T.1
  • 14
    • 84876515155 scopus 로고    scopus 로고
    • Jameson, A. (2004). More than the sum of its members: challenges for group recommender systems. In Proceedings of the international working conference on advanced visual interfaces, Gallipoli, Italy.
  • 15
    • 33748082327 scopus 로고    scopus 로고
    • An evolutionary approach to the combination of multiple classifiers to predict a stock price index
    • Kim M.-J., Min S.-H., and Han I. An evolutionary approach to the combination of multiple classifiers to predict a stock price index. Expert Systems with Applications 31 2 (2006) 241-247
    • (2006) Expert Systems with Applications , vol.31 , Issue.2 , pp. 241-247
    • Kim, M.-J.1    Min, S.-H.2    Han, I.3
  • 16
    • 0031236550 scopus 로고    scopus 로고
    • The InfoFinder agent: learning user interests through heuristic phrase extraction
    • Krulwich B., and Burkey C. The InfoFinder agent: learning user interests through heuristic phrase extraction. IEEE Expert-Intelligent Systems, Their Applications 12 5 (1997) 22-27
    • (1997) IEEE Expert-Intelligent Systems, Their Applications , vol.12 , Issue.5 , pp. 22-27
    • Krulwich, B.1    Burkey, C.2
  • 17
    • 37349083281 scopus 로고    scopus 로고
    • Lang, K. (1995). NewsWeeder: Learning to filter netnews. In Proceedings of the 12th international conference on machine learning (pp. 331-339). San Francisco.
  • 18
    • 0037252945 scopus 로고    scopus 로고
    • Amazon.com recommendation Item-to-item collaborative filtering
    • Linden G., Smith B., and York J. Amazon.com recommendation Item-to-item collaborative filtering. IEEE Internet Computing 7 1 (2003) 76-80
    • (2003) IEEE Internet Computing , vol.7 , Issue.1 , pp. 76-80
    • Linden, G.1    Smith, B.2    York, J.3
  • 19
    • 37349093152 scopus 로고    scopus 로고
    • Masthoff, J. (2002). Modeling a Group of Television Viewers. In Proceedings of the workshop future TV in intelligent tutoring systems conference (pp. 34-42).
  • 20
    • 0032282347 scopus 로고    scopus 로고
    • McCarthy, J. F., & Anagnost, T. D. (1998). MusicFX: an arbiter of group preferences for computer supported collaborative workouts. In Proceedings of the ACM conference on computer supported cooperative work (pp. 363-372).
  • 21
    • 11244275592 scopus 로고    scopus 로고
    • Detection of the customer time-variant pattern for improving recommender systems
    • Min S.-H., and Han I. Detection of the customer time-variant pattern for improving recommender systems. Expert Systems with Applications 28 2 (2005) 189-199
    • (2005) Expert Systems with Applications , vol.28 , Issue.2 , pp. 189-199
    • Min, S.-H.1    Han, I.2
  • 22
    • 37349085557 scopus 로고    scopus 로고
    • Mooney, R. J., & Roy, L. (1999). Content-based book recommending using learning for text categorization. In ACM SIGIR '99 Workshop Recommender Systems: Algorithms and Evaluation, 195-240.
  • 23
    • 37349097445 scopus 로고    scopus 로고
    • O'Connor, M., Cosley, D., Konstan, J., & Riedl, J. (2001). PolyLens: a recommender system for groups of users. In Proceedings of the European conference on computer-supported cooperative work (pp. 199-218). Germany.
  • 24
    • 85030174634 scopus 로고    scopus 로고
    • Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., & Riedl, J. (1994). GroupLens: An open architecture for collaborative filtering of netnews. In Proceedings of the ACM conference on computer-supported cooperative work (pp. 175-186).
  • 26
    • 85052617391 scopus 로고    scopus 로고
    • Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001). Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th international conference on world wide web (pp. 285-295).


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.