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Volumn , Issue , 2014, Pages 1186-1195

FEMA: Flexible evolutionary multi-faceted analysis for dynamic behavioral pattern discovery

Author keywords

behavior modeling; behavioral pattern; evolutionary analysis; flexible regularizers; tensor factorization

Indexed keywords


EID: 84907022679     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2623330.2623644     Document Type: Conference Paper
Times cited : (52)

References (35)
  • 2
    • 85007200249 scopus 로고    scopus 로고
    • Making recommendations from multiple domains
    • W. Chen, W. Hsu, and M. L. Lee. Making recommendations from multiple domains. In KDD'13, pages 892-900.
    • KDD'13 , pp. 892-900
    • Chen, W.1    Hsu, W.2    Lee, M.L.3
  • 3
    • 84883091912 scopus 로고    scopus 로고
    • Modeling user's receptiveness over time for recommendation
    • W. Chen, W. Hsu, and M. L. Lee. Modeling user's receptiveness over time for recommendation. In SIGIR'13, pages 373-382.
    • SIGIR'13 , pp. 373-382
    • Chen, W.1    Hsu, W.2    Lee, M.L.3
  • 4
    • 38049150410 scopus 로고    scopus 로고
    • Regularized alternating least squares algorithms for non-negative matrix/tensor factorization
    • A. Cichocki and R. Zdunek. Regularized alternating least squares algorithms for non-negative matrix/tensor factorization. In Advances in Neural Networks-ISNN 2007, pages 793-802.
    • Advances in Neural Networks-ISNN 2007 , pp. 793-802
    • Cichocki, A.1    Zdunek, R.2
  • 5
    • 84961329426 scopus 로고    scopus 로고
    • Cascading outbreak prediction in networks: A data-driven approach
    • P. Cui, S. Jin, L. Yu, F. Wang, W. Zhu, and S. Yang. Cascading outbreak prediction in networks: a data-driven approach. In KDD'13, pages 901-909.
    • KDD'13 , pp. 901-909
    • Cui, P.1    Jin, S.2    Yu, L.3    Wang, F.4    Zhu, W.5    Yang, S.6
  • 6
    • 80052124916 scopus 로고    scopus 로고
    • Who should share what? Item-level social influence prediction for users and posts ranking
    • P. Cui, F. Wang, S. Liu, M. Ou, S. Yang, and L. Sun. Who should share what? item-level social influence prediction for users and posts ranking. In SIGIR'11, pages 185-194.
    • SIGIR'11 , pp. 185-194
    • Cui, P.1    Wang, F.2    Liu, S.3    Ou, M.4    Yang, S.5    Sun, L.6
  • 7
    • 34250727580 scopus 로고    scopus 로고
    • The relationship between precision-recall and roc curves
    • J. Davis and M. Goadrich. The relationship between precision-recall and roc curves. In ICML'06, pages 233-240.
    • ICML'06 , pp. 233-240
    • Davis, J.1    Goadrich, M.2
  • 9
    • 79952552980 scopus 로고    scopus 로고
    • Temporal link prediction using matrix and tensor factorizations
    • D. M. Dunlavy, T. G. Kolda, and E. Acar. Temporal link prediction using matrix and tensor factorizations. TKDD, 5(2):10, 2011.
    • (2011) TKDD , vol.5 , Issue.2 , pp. 10
    • Dunlavy, D.M.1    Kolda, T.G.2    Acar, E.3
  • 10
    • 84891773848 scopus 로고    scopus 로고
    • Personalized recommendation via cross-domain triadic factorization
    • L. Hu, J. Cao, G. Xu, L. Cao, Z. Gu, and C. Zhu. Personalized recommendation via cross-domain triadic factorization. In WWW'13, pages 595-606.
    • WWW'13 , pp. 595-606
    • Hu, L.1    Cao, J.2    Xu, G.3    Cao, L.4    Gu, Z.5    Zhu, C.6
  • 12
    • 84871038251 scopus 로고    scopus 로고
    • Social recommendation across multiple relational domains
    • M. Jiang, P. Cui, F. Wang, Q. Yang, W. Zhu, and S. Yang. Social recommendation across multiple relational domains. In CIKM'12, pages 1422-1431.
    • CIKM'12 , pp. 1422-1431
    • Jiang, M.1    Cui, P.2    Wang, F.3    Yang, Q.4    Zhu, W.5    Yang, S.6
  • 13
    • 84866052446 scopus 로고    scopus 로고
    • Gigatensor: Scaling tensor analysis up by 100 times-algorithms and discoveries
    • U. Kang, E. Papalexakis, A. Harpale, and C. Faloutsos. Gigatensor: scaling tensor analysis up by 100 times-algorithms and discoveries. In KDD'12, pages 316-324.
    • KDD'12 , pp. 316-324
    • Kang, U.1    Papalexakis, E.2    Harpale, A.3    Faloutsos, C.4
  • 14
    • 0035747556 scopus 로고    scopus 로고
    • Evaluation of item-based top-n recommendation algorithms
    • G. Karypis. Evaluation of item-based top-n recommendation algorithms. In CIKM'01, pages 247-254.
    • CIKM'01 , pp. 247-254
    • Karypis, G.1
  • 16
    • 68649096448 scopus 로고    scopus 로고
    • Tensor decompositions and applications
    • T. G. Kolda and B. W. Bader. Tensor decompositions and applications. SIAM review, 51(3):455-500, 2009.
    • (2009) SIAM Review , vol.51 , Issue.3 , pp. 455-500
    • Kolda, T.G.1    Bader, B.W.2
  • 17
    • 67049173946 scopus 로고    scopus 로고
    • Scalable tensor decompositions for multi-aspect data mining
    • T. G. Kolda and J. Sun. Scalable tensor decompositions for multi-aspect data mining. In ICDM'08, pages 363-372.
    • ICDM'08 , pp. 363-372
    • Kolda, T.G.1    Sun, J.2
  • 18
    • 85008044987 scopus 로고    scopus 로고
    • Matrix factorization techniques for recommender systems
    • Y. Koren, R. Bell, and C. Volinsky. Matrix factorization techniques for recommender systems. Computer, 42(8):30-37, 2009.
    • (2009) Computer , vol.42 , Issue.8 , pp. 30-37
    • Koren, Y.1    Bell, R.2    Volinsky, C.3
  • 19
    • 78651275223 scopus 로고    scopus 로고
    • Mining topic-level influence in heterogeneous networks
    • L. Liu, J. Tang, J. Han, M. Jiang, and S. Yang. Mining topic-level influence in heterogeneous networks. In CIKM'10, pages 199-208.
    • CIKM'10 , pp. 199-208
    • Liu, L.1    Tang, J.2    Han, J.3    Jiang, M.4    Yang, S.5
  • 20
    • 84875453765 scopus 로고    scopus 로고
    • Discovery and analysis of evolving topical social discussions on unstructured microblogs
    • K. Narang, S. Nagar, S. Mehta, L. Subramaniam, and K. Dey. Discovery and analysis of evolving topical social discussions on unstructured microblogs. In Advances in Information Retrieval, pages 545-556. 2013.
    • (2013) Advances in Information Retrieval , pp. 545-556
    • Narang, K.1    Nagar, S.2    Mehta, S.3    Subramaniam, L.4    Dey, K.5
  • 23
    • 77950902603 scopus 로고    scopus 로고
    • Pairwise interaction tensor factorization for personalized tag recommendation
    • S. Rendle and L. Schmidt-Thieme. Pairwise interaction tensor factorization for personalized tag recommendation. In WSDM'10, pages 81-90.
    • WSDM'10 , pp. 81-90
    • Rendle, S.1    Schmidt-Thieme, L.2
  • 26
    • 55149108152 scopus 로고    scopus 로고
    • Incremental tensor analysis: Theory and applications
    • J. Sun, D. Tao, S. Papadimitriou, P. S. Yu, and C. Faloutsos. Incremental tensor analysis: Theory and applications. TKDD, 2(3):11, 2008.
    • (2008) TKDD , vol.2 , Issue.3 , pp. 11
    • Sun, J.1    Tao, D.2    Papadimitriou, S.3    Yu, P.S.4    Faloutsos, C.5
  • 27
    • 34250676942 scopus 로고    scopus 로고
    • Cubesvd: A novel approach to personalized web search
    • J.-T. Sun, H.-J. Zeng, H. Liu, Y. Lu, and Z. Chen. Cubesvd: a novel approach to personalized web search. In WWW'05,pages 382-390.
    • WWW'05 , pp. 382-390
    • Sun, J.-T.1    Zeng, H.-J.2    Liu, H.3    Lu, Y.4    Chen, Z.5
  • 28
    • 84961863348 scopus 로고    scopus 로고
    • Co-evolution of multi-typed objects in dynamic star networks
    • Y. Sun, J. Tang, J. Han, C. Chen, and M. Gupta. Co-evolution of multi-typed objects in dynamic star networks. TKDE, 2013.
    • (2013) TKDE
    • Sun, Y.1    Tang, J.2    Han, J.3    Chen, C.4    Gupta, M.5
  • 29
    • 63749113841 scopus 로고    scopus 로고
    • Tag recommendations based on tensor dimensionality reduction
    • P. Symeonidis, A. Nanopoulos, and Y. Manolopoulos. Tag recommendations based on tensor dimensionality reduction. In RecSys'08, pages 43-50.
    • RecSys'08 , pp. 43-50
    • Symeonidis, P.1    Nanopoulos, A.2    Manolopoulos, Y.3
  • 30
    • 84880115438 scopus 로고    scopus 로고
    • imet: Interactive metric learning in healthcare applications
    • F. Wang, J. Sun, J. Hu, and S. Ebadollahi. imet: interactive metric learning in healthcare applications. In SDM'11, pages 944-955.
    • SDM'11 , pp. 944-955
    • Wang, F.1    Sun, J.2    Hu, J.3    Ebadollahi, S.4
  • 31
    • 80055037014 scopus 로고    scopus 로고
    • Towards evolutionary nonnegative matrix factorization
    • F. Wang, H. Tong, and C.-Y. Lin. Towards evolutionary nonnegative matrix factorization. In AAAI'11, pages 501-506.
    • AAAI'11 , pp. 501-506
    • Wang, F.1    Tong, H.2    Lin, C.-Y.3
  • 32
    • 84904553274 scopus 로고    scopus 로고
    • Understanding evolution of research themes: A probabilistic generative model for citations
    • X. Wang, C. Zhai, and D. Roth. Understanding evolution of research themes: a probabilistic generative model for citations. In KDD'13, pages 1115-1123.
    • KDD'13 , pp. 1115-1123
    • Wang, X.1    Zhai, C.2    Roth, D.3
  • 33
    • 77956220287 scopus 로고    scopus 로고
    • Temporal recommendation on graphs via long-and short-term preference fusion
    • L. Xiang, Q. Yuan, S. Zhao, L. Chen, X. Zhang, Q. Yang, and J. Sun. Temporal recommendation on graphs via long-and short-term preference fusion. In KDD'10, pages 723-732.
    • KDD'10 , pp. 723-732
    • Xiang, L.1    Yuan, Q.2    Zhao, S.3    Chen, L.4    Zhang, X.5    Yang, Q.6    Sun, J.7
  • 34
    • 84992119955 scopus 로고    scopus 로고
    • Who, where, when and what: Discover spatio-temporal topics for twitter users
    • Q. Yuan, G. Cong, Z. Ma, A. Sun, and N. M. Thalmann. Who, where, when and what: Discover spatio-temporal topics for twitter users. In KDD'13, pages 605-613.
    • KDD'13 , pp. 605-613
    • Yuan, Q.1    Cong, G.2    Ma, Z.3    Sun, A.4    Thalmann, N.M.5
  • 35
    • 84976493759 scopus 로고    scopus 로고
    • Collaborative matrix factorization with multiple similarities for predicting drug-target interactions
    • X. Zheng, H. Ding, H. Mamitsuka, and S. Zhu. Collaborative matrix factorization with multiple similarities for predicting drug-target interactions. In KDD'13, pages 1025-1033.
    • KDD'13 , pp. 1025-1033
    • Zheng, X.1    Ding, H.2    Mamitsuka, H.3    Zhu, S.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.