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Volumn 5872 LNCS, Issue , 2009, Pages 604-609

Semantically enhanced recommender systems

Author keywords

Ontologies; Personalisation; Recommender systems; User modelling

Indexed keywords

PERSONALISATION; RECOMMENDER SYSTEMS; USER MODELLING; USER PROFILE; WEB PERSONALIZATION;

EID: 78650754882     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-05290-3_74     Document Type: Conference Paper
Times cited : (22)

References (9)
  • 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., Tuzhilin, A.: Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734-749 (2005)
    • (2005) IEEE Trans. Knowl. Data Eng. , vol.17 , Issue.6 , pp. 734-749
    • Adomavicius, G.1    Tuzhilin, A.2
  • 2
    • 23144465959 scopus 로고    scopus 로고
    • Semantically Enhanced Collaborative Filtering on the Web
    • Berendt, B., Hotho, A., Mladenič, D., van Someren, M., Spiliopoulou, M., Stumme, G. (eds.) EWMF 2003. Springer, Heidelberg
    • Mobasher, B., Jin, X., Zhou, Y.: Semantically Enhanced Collaborative Filtering on the Web. In: Berendt, B., Hotho, A., Mladenič, D., van Someren, M., Spiliopoulou, M., Stumme, G. (eds.) EWMF 2003. LNCS (LNAI), vol. 3209, pp. 57-76. Springer, Heidelberg (2004)
    • (2004) LNCS (LNAI) , vol.3209 , pp. 57-76
    • Mobasher, B.1    Jin, X.2    Zhou, Y.3
  • 5
    • 34548787451 scopus 로고    scopus 로고
    • Exploiting Semantic Descriptions of Products and User Profiles for Recommender Systems
    • Liu, P., Nie, G., Chen, D.: Exploiting Semantic Descriptions of Products and User Profiles for Recommender Systems. Computational Intelligence and Data Mining, 179-185 (2007)
    • (2007) Computational Intelligence and Data Mining , pp. 179-185
    • Liu, P.1    Nie, G.2    Chen, D.3
  • 7
    • 67650695966 scopus 로고    scopus 로고
    • Movie Recommender: Semantically Enriched Unified Relevance Model for Rating Prediction in Collaborative Filtering
    • Boughanem, M., et al. (eds.) ECIR 2009. Springer, Heidelberg
    • Moshfeghi, Y., Agarwal, D., Piwowarski, B., Jose, J.M.: Movie Recommender: Semantically Enriched Unified Relevance Model for Rating Prediction in Collaborative Filtering. In: Boughanem, M., et al. (eds.) ECIR 2009. LNCS, vol. 5478, pp. 54-65. Springer, Heidelberg (2009)
    • (2009) LNCS , vol.5478 , pp. 54-65
    • Moshfeghi, Y.1    Agarwal, D.2    Piwowarski, B.3    Jose, J.M.4
  • 8
    • 2942597326 scopus 로고    scopus 로고
    • Industry Report: Amazon.com Recommendations: Item-to-Item Collaborative Filtering
    • Linden, G., Smith, B., York, J.: Industry Report: Amazon.com Recommendations: Item-to-Item Collaborative Filtering. IEEE Distributed Systems Online 4(1) (2003)
    • (2003) IEEE Distributed Systems Online , vol.4 , Issue.1
    • Linden, G.1    Smith, B.2    York, J.3
  • 9
    • 3042821101 scopus 로고    scopus 로고
    • Item-based top-n recommendation algorithms
    • Deshpande, M., Karypis, G.: Item-based top-n recommendation algorithms. ACM Trans. Inf. Sys. 22(1), 143-177 (2004)
    • (2004) ACM Trans. Inf. Sys. , vol.22 , Issue.1 , pp. 143-177
    • Deshpande, M.1    Karypis, G.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.