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Volumn , Issue , 2010, Pages 61-65

Topic-based personalized recommendation for collaborative tagging system

Author keywords

Collaborative tagging; Latent topic models; Personalization; Recommendation

Indexed keywords

COLLABORATIVE TAGGING; DATA SPARSENESS; DATA SPARSITY; GENERATIVE MODEL; HETEROGENEOUS USERS; IMPLICIT SEMANTICS; INFORMATION SPACES; LATENT DIRICHLET ALLOCATIONS; LATENT TOPIC MODEL; ONLINE RESOURCES; PERSONALIZATIONS; PERSONALIZED RECOMMENDATION; RESOURCE DESCRIPTION; USERS' INTERESTS; WEB 2.0;

EID: 77954892603     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1810617.1810629     Document Type: Conference Paper
Times cited : (9)

References (13)
  • 2
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    • Integrating tags in a semantic content-based recommender
    • (Lausanne, Switzerland, October 23-25, 2008). RecSys'08. ACM, New York, NY
    • De Gemmis, M., Lops, P., Semeraro, G., and Basile, P. 2008. Integrating tags in a semantic content-based recommender. In proceedings of the 2008 ACM Conference on Recommender Systems (Lausanne, Switzerland, October 23-25, 2008). RecSys'08. ACM, New York, NY, 163-170.
    • (2008) Proceedings of the 2008 ACM Conference on Recommender Systems , pp. 163-170
    • De Gemmis, M.1    Lops, P.2    Semeraro, G.3    Basile, P.4
  • 3
    • 56749171376 scopus 로고    scopus 로고
    • Tag-aware recommender systems by fusion of collaborative filtering algorithms
    • (Fortaleza, Brazil, March 16-20, 2008). SAC'08. ACM, New York, NY
    • Tso-Sutter, K.H., Marinho, L.B., and Schmidt-Thieme, L., 2008. Tag-aware recommender systems by fusion of collaborative filtering algorithms. In the Proceedings of ACM Symposium on Applied Computing (Fortaleza, Brazil, March 16-20, 2008). SAC'08. ACM, New York, NY, 1995-1999.
    • (2008) The Proceedings of ACM Symposium on Applied Computing , pp. 1995-1999
    • Tso-Sutter, K.H.1    Marinho, L.B.2    Schmidt-Thieme, L.3
  • 6
    • 67650665736 scopus 로고    scopus 로고
    • A hybrid approach to item recommendation in folksonomies
    • (Barcelona, Spain, February 09 - 09, 2009). ESAIR '09. ACM, New York, NY, DOI=http://doi.acm.org/10.1145/1506250.1506255
    • Wetzker, R., Umbrath, W., and Said, A. 2009. A hybrid approach to item recommendation in folksonomies. In Proceedings of the WSDM '09 Workshop on Exploiting Semantic Annotations in information Retrieval (Barcelona, Spain, February 09 - 09, 2009). ESAIR '09. ACM, New York, NY, 25-29. DOI=http://doi.acm.org/10.1145/1506250.1506255.
    • (2009) Proceedings of the WSDM '09 Workshop on Exploiting Semantic Annotations in Information Retrieval , pp. 25-29
    • Wetzker, R.1    Umbrath, W.2    Said, A.3
  • 7
    • 63449133288 scopus 로고    scopus 로고
    • Social ranking: Uncovering relevant content using tag-based recommender systems
    • (Lausanne, Switzerland, October 23 - 25, 2008). RecSys '08. ACM, New York, NY, DOI=http://doi.acm.org/10.1145/1454008.1454018
    • Zanardi, V. and Capra, L. 2008. Social ranking: uncovering relevant content using tag-based recommender systems. In Proceedings of the 2008 ACM Conference on Recommender Systems (Lausanne, Switzerland, October 23 - 25, 2008). RecSys '08. ACM, New York, NY, 51-58. DOI=http://doi.acm.org/10.1145/ 1454008.1454018.
    • (2008) Proceedings of the 2008 ACM Conference on Recommender Systems , pp. 51-58
    • Zanardi, V.1    Capra, L.2
  • 9
    • 52449112950 scopus 로고    scopus 로고
    • Leveraging tagging to model user interests in del.icio.us
    • Stoyanovich, J., Amer-Yahia, S., Marlow, C. and Yu, C., 2008. Leveraging Tagging to Model User Interests in del.icio.us. In AAAI-SIP.
    • (2008) AAAI-SIP
    • Stoyanovich, J.1    Amer-Yahia, S.2    Marlow, C.3    Yu, C.4
  • 11
    • 77954942539 scopus 로고    scopus 로고
    • Tag-LDA for scalable real-time tag recommendation
    • Si, X. and Sun, M., 2009.Tag-LDA for Scalable Real-time Tag Recommendation, Journal of Computational Information Systems. 6(1):23-31.
    • (2009) Journal of Computational Information Systems , vol.6 , Issue.1 , pp. 23-31
    • Si, X.1    Sun, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.