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Volumn , Issue , 2011, Pages 285-288

Using Wikipedia to boost collaborative filtering techniques

Author keywords

cold start problem; collaborative filtering; recommender systems; Wikipedia

Indexed keywords

ACCURATE PREDICTION; COLD START PROBLEMS; COLLABORATIVE FILTERING; COLLABORATIVE FILTERING TECHNIQUES; DATA SETS; USER RATING; WIKIPEDIA;

EID: 82555183086     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2043932.2043984     Document Type: Conference Paper
Times cited : (19)

References (9)
  • 1
    • 0029194949 scopus 로고
    • Pointing the way: Active collaborative filtering
    • ACM Press/Addison-Wesley Publishing Co.: Denver, Colorado, United States
    • Maltz, D. and K. Ehrlich, 1995. Pointing the way: active collaborative filtering, in Proceedings of the SIGCHI conference on Human factors in computing systems, ACM Press/Addison-Wesley Publishing Co.: Denver, Colorado, United States. p. 202-209.
    • (1995) Proceedings of the SIGCHI Conference on Human Factors in Computing Systems , pp. 202-209
    • Maltz, D.1    Ehrlich, K.2
  • 2
    • 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 A. Tuzhilin, 2005. 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) IEEE Transactions on Knowledge and Data Engineering , vol.17 , Issue.6
    • Adomavicius, G.1    Tuzhilin, A.2
  • 3
    • 33749244569 scopus 로고    scopus 로고
    • Content-Boosted Collaborative Filtering for Improved Recommendations
    • Melville, P., R.J. Mooney, and R. Nagarajan. 2002. Content-Boosted Collaborative Filtering for Improved Recommendations. AAAI-02 Proceedings,
    • (2002) AAAI-02 Proceedings
    • Melville, P.1    Mooney, R.J.2    Nagarajan, R.3
  • 5
    • 72249111093 scopus 로고    scopus 로고
    • Knowledge infusion into content-based recommender systems
    • ACM: New York, New York, USA
    • Semeraro, G., et al. 2009. Knowledge infusion into content-based recommender systems. in Proceedings of the third ACM conference on Recommender systems, ACM: New York, New York, USA. p. 301-304.
    • (2009) Proceedings of the Third ACM Conference on Recommender Systems , pp. 301-304
    • Semeraro, G.1
  • 7
    • 79551648093 scopus 로고    scopus 로고
    • A probabilistic approach to semantic collaborative filtering using world knowledge
    • Lee, J.w., Lee S.g., and Kim, H.j. 2011. A probabilistic approach to semantic collaborative filtering using world knowledge. Journal of Information Science. 37(1): p. 49-66.
    • (2011) Journal of Information Science. , vol.37 , Issue.1 , pp. 49-66
    • Lee, J.W.1    Lee, S.G.2    Kim, H.J.3
  • 9
    • 85052617391 scopus 로고    scopus 로고
    • Item-based collaborative filtering recommendation algorithms
    • ACM: Hong Kong, Hong Kong
    • Sarwar, B., et al. 2001. Item-based collaborative filtering recommendation algorithms, in Proceedings of the 10th international conference on World Wide Web, ACM: Hong Kong, Hong Kong. p. 285-295
    • (2001) Proceedings of the 10th International Conference on World Wide Web , pp. 285-295
    • Sarwar, B.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.