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Volumn , Issue , 2012, Pages 2527-2530

Climbing the app wall: Enabling mobile app discovery through context-aware recommendations

Author keywords

collaborative filtering; implicit feedback; mobile apps; mobile recommendation; tensor factorization, context

Indexed keywords

COLLABORATIVE FILTERING; IMPLICIT FEEDBACK; MOBILE APPS; MOBILE RECOMMENDATION; TENSOR FACTORIZATION;

EID: 84871090829     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2396761.2398683     Document Type: Conference Paper
Times cited : (90)

References (12)
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    • M. Böhmer, B. Hecht, J. Schöning, A. Krüger, and G. Bauer. Falling asleep with angry birds, facebook and kindle - a large scale study on mobile application usage. In Proc. of Mobile HCI '11). ACM, 8 2011.
    • (2011) Proc. of Mobile HCI '11
    • Böhmer, M.1    Hecht, B.2    Schöning, J.3    Krüger, A.4    Bauer, G.5
  • 2
    • 80054835893 scopus 로고    scopus 로고
    • Contextualizing mobile applications for context-aware recommendation
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    • Böhmer, M.1    Prinz, M.2    Bauer, G.3
  • 4
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    • Understanding the intent behind mobile information needs
    • ACM
    • K. Church and B. Smyth. Understanding the intent behind mobile information needs. In Proceedings of IUI '09, pages 247-256. ACM, 2009.
    • (2009) Proceedings of IUI '09 , pp. 247-256
    • Church, K.1    Smyth, B.2
  • 5
    • 78649914423 scopus 로고    scopus 로고
    • Performance of recommender algorithms on top-n recommendation tasks
    • P. Cremonesi, Y. Koren, and R. Turrin. Performance of recommender algorithms on top-n recommendation tasks. In Proc. of RecSys '10, pages 39-46, 2010.
    • (2010) Proc. of RecSys '10 , pp. 39-46
    • Cremonesi, P.1    Koren, Y.2    Turrin, R.3
  • 6
    • 85162707890 scopus 로고
    • The expression of a tensor or a polyadic as a sum of products
    • F. L. Hitchcock. The expression of a tensor or a polyadic as a sum of products. Journal of Math. and Physics, 6, 1927.
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    • Hitchcock, F.L.1
  • 7
    • 67049164166 scopus 로고    scopus 로고
    • Collaborative filtering for implicit feedback datasets
    • Washington, DC, USA, IEEE Computer Society
    • Y. Hu, Y. Koren, and C. Volinsky. Collaborative filtering for implicit feedback datasets. In Proc. of ICDM '08, pages 263-272, Washington, DC, USA, 2008. IEEE Computer Society.
    • (2008) Proc. of ICDM '08 , pp. 263-272
    • Hu, Y.1    Koren, Y.2    Volinsky, C.3
  • 8
    • 78649941975 scopus 로고    scopus 로고
    • Multiverse recommendation: N-dimensional tensor factorization for context-aware collaborative filtering
    • A. Karatzoglou, X. Amatriain, L. Baltrunas, and N. Oliver. Multiverse recommendation: n-dimensional tensor factorization for context-aware collaborative filtering. In Proc. of RecSys '10, pages 79-86, 2010.
    • (2010) Proc. of RecSys '10 , pp. 79-86
    • Karatzoglou, A.1    Amatriain, X.2    Baltrunas, L.3    Oliver, N.4
  • 9
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    • Mind the gaps: Weighting the unknown in large-scale one-class collaborative filtering
    • New York, NY, USA, ACM
    • R. Pan and M. Scholz. Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering. In Proc. of KDD '09, pages 667-676, New York, NY, USA, 2009. ACM.
    • (2009) Proc. of KDD '09 , pp. 667-676
    • Pan, R.1    Scholz, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.