메뉴 건너뛰기




Volumn , Issue , 2013, Pages 695-703

CoSelect: Feature selection with instance selection for social media data

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; DATA MINING; SOCIAL NETWORKING (ONLINE);

EID: 84942434123     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972832.77     Document Type: Conference Paper
Times cited : (30)

References (41)
  • 1
    • 0036161259 scopus 로고    scopus 로고
    • Gene selection for cancer classification using support vector machines
    • I. Guyon, J.Weston, S. Barnhill, and V. Vapnik, "Gene selection for cancer classification using support vector machines," Machine learning, 2002.
    • (2002) Machine Learning
    • Guyon, I.1    Weston, J.2    Barnhill, S.3    Vapnik, V.4
  • 2
    • 0038155829 scopus 로고    scopus 로고
    • Some notes on alternating optimization
    • Bezdek, J. and Hathaway, R., "Some notes on alternating optimization", in AFSS, 2002.
    • (2002) AFSS
    • Bezdek, J.1    Hathaway, R.2
  • 4
    • 84866052116 scopus 로고    scopus 로고
    • Unsupervised feature selection for linked social media data
    • J. Tang, and H. Liu, "Unsupervised feature selection for linked social media data," in KDD, 2012.
    • (2012) KDD
    • Tang, J.1    Liu, H.2
  • 6
    • 84880191846 scopus 로고    scopus 로고
    • Feature selection with linked data in social media
    • J. Tang and H. Liu, "Feature selection with linked data in social media," in SDM, 2012.
    • (2012) SDM
    • Tang, J.1    Liu, H.2
  • 7
    • 84874223723 scopus 로고    scopus 로고
    • Exploiting homophily effect for trust prediction
    • J. Tang, H. Gao, X. Hu and H. Liu, "Exploiting Homophily Effect for Trust Prediction," in WSDM,2013.
    • (2013) WSDM
    • Tang, J.1    Gao, H.2    Hu, X.3    Liu, H.4
  • 8
    • 85167457112 scopus 로고    scopus 로고
    • ET-LDA: Joint topic modeling for aligning events and their twitter feedback
    • Y. Hu, A. John, F. Wang,and S. Kambhampati. ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback. In AAAI, 2012.
    • (2012) AAAI
    • Hu, Y.1    John, A.2    Wangand, F.3    Kambhampati, S.4
  • 9
    • 1942450651 scopus 로고    scopus 로고
    • Linkage and autocorrelation cause feature selection bias in relational learning
    • D. Jensen and J. Neville, "Linkage and autocorrelation cause feature selection bias in relational learning," in ICML, 2002.
    • (2002) ICML
    • Jensen, D.1    Neville, J.2
  • 12
    • 0141688336 scopus 로고    scopus 로고
    • On issues of instance selection
    • H. Liu and H. Motoda, "On issues of instance selection," DMKD, 2002.
    • (2002) DMKD
    • Liu, H.1    Motoda, H.2
  • 15
    • 80053145416 scopus 로고    scopus 로고
    • Multi-task feature learning via efficient l 2, 1-norm minimization
    • J. Liu, S. Ji, and J. Ye, "Multi-task feature learning via efficient l 2, 1-norm minimization," in UAI, 2009.
    • (2009) UAI
    • Liu, J.1    Ji, S.2    Ye, J.3
  • 16
    • 33749255817 scopus 로고    scopus 로고
    • R 1-PCA: Rotational invariant l 1-norm principal component analysis for robust subspace factorization
    • C. Ding, D. Zhou, X. He, and H. Zha, "R 1-pca: rotational invariant l 1-norm principal component analysis for robust subspace factorization," in ICML, 2006.
    • (2006) ICML
    • Ding, C.1    Zhou, D.2    He, X.3    Zha, H.4
  • 18
    • 84865437346 scopus 로고    scopus 로고
    • Non-negative residual matrix factorization with application to graph anomaly detection
    • H. Tong and C. Lin, "Non-negative residual matrix factorization with application to graph anomaly detection." SDM, 2011.
    • (2011) SDM
    • Tong, H.1    Lin, C.2
  • 20
    • 85135939782 scopus 로고    scopus 로고
    • Efficient and robust feature selection via joint l21-norms minimization
    • F. Nie, H. Huang, X. Cai, and C. Ding, "Efficient and robust feature selection via joint l21-norms minimization." in NIPS, 2010.
    • (2010) NIPS
    • Nie, F.1    Huang, H.2    Cai, X.3    Ding, C.4
  • 21
    • 79951756832 scopus 로고    scopus 로고
    • Discovering overlapping groups in social media
    • X. Wang, L. Tang, H. Gao, and H. Liu, "Discovering overlapping groups in social media," in ICDM,2010.
    • (2010) ICDM
    • Wang, X.1    Tang, L.2    Gao, H.3    Liu, H.4
  • 22
    • 71049136197 scopus 로고    scopus 로고
    • Metafac: Community discovery via relational hypergraph factorization
    • Y. Lin, J. Sun, P. Castro, R. Konuru, H. Sundaram, and A. Kelliher, "Metafac: community discovery via relational hypergraph factorization," in KDD, 2009.
    • (2009) KDD
    • Lin, Y.1    Sun, J.2    Castro, P.3    Konuru, R.4    Sundaram, H.5    Kelliher, A.6
  • 23
    • 85158826352 scopus 로고    scopus 로고
    • Efficient spectral feature selection with minimum redundancy
    • Z. Zhao, L. Wang, and H. Liu, "Efficient spectral feature selection with minimum redundancy," in AAAI, 2010.
    • (2010) AAAI
    • Zhao, Z.1    Wang, L.2    Liu, H.3
  • 24
    • 65149104302 scopus 로고    scopus 로고
    • Spectral feature selection for supervised and unsupervised learning
    • Z. Zhao and H. Liu, "Spectral feature selection for supervised and unsupervised learning," in ICML, 2007.
    • (2007) ICML
    • Zhao, Z.1    Liu, H.2
  • 25
    • 50949133669 scopus 로고    scopus 로고
    • Liblinear: A library for large linear classification
    • R. Fan, K. Chang, C. Hsieh, X. Wang, and C. Lin, "Liblinear: A library for large linear classification," in JMLR, 2008.
    • (2008) JMLR
    • Fan, R.1    Chang, K.2    Hsieh, C.3    Wang, X.4    Lin, C.5
  • 27
    • 80053144252 scopus 로고    scopus 로고
    • Generalized fisher score for feature selection
    • Q. Gu, Z. Li, and J. Han, "Generalized fisher score for feature selection," in UAI, 2011.
    • (2011) UAI
    • Gu, Q.1    Li, Z.2    Han, J.3
  • 29
    • 17044405923 scopus 로고    scopus 로고
    • Toward integrating feature selection algorithms for classification and clustering
    • H. Liu and L. Yu, "Toward integrating feature selection algorithms for classification and clustering," in TKDE, 2005.
    • (2005) TKDE
    • Liu, H.1    Yu, L.2
  • 30
    • 0141990695 scopus 로고    scopus 로고
    • Theoretical and empirical analysis of ReliefF and RReliefF
    • M. Robnik-Šikonja and I. Kononenko, "Theoretical and empirical analysis of ReliefF and RReliefF," in Machine learning, 2003.
    • (2003) Machine Learning
    • Robnik-Šikonja, M.1    Kononenko, I.2
  • 31
    • 24344458137 scopus 로고    scopus 로고
    • Feature selection based on mutual information: Criteria of max-dependency, max-relevance, and min-redundancy
    • H. Peng, F. Long, and C. Ding, "Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy," in TPAMI, 2005.
    • (2005) TPAMI
    • Peng, H.1    Long, F.2    Ding, C.3
  • 32
    • 33845535234 scopus 로고    scopus 로고
    • Laplacian score for feature selection
    • X. He, D. Cai, and P. Niyogi, "Laplacian score for feature selection," in NIPS, 2006.
    • (2006) NIPS
    • He, X.1    Cai, D.2    Niyogi, P.3
  • 33
    • 84874258367 scopus 로고    scopus 로고
    • Exploiting social relations for sentiment analysis in microblogging
    • X. Hu, L. Tang, J. Tang and H. Liu, "Exploiting Social Relations for Sentiment Analysis in Microblogging," in WSDM, 2013.
    • (2013) WSDM
    • Hu, X.1    Tang, L.2    Tang, J.3    Liu, H.4
  • 34
    • 26444454606 scopus 로고    scopus 로고
    • Feature selection for unsupervised learning
    • J. Dy and C. Brodley, "Feature selection for unsupervised learning," in JMLR, 2004.
    • (2004) JMLR
    • Dy, J.1    Brodley, C.2
  • 35
    • 33645957324 scopus 로고    scopus 로고
    • Bayesian feature and model selection for Gaussian mixture models
    • C. Constantinopoulos, M. Titsias, and A. Likas, "Bayesian feature and model selection for gaussian mixture models," in TPAMI, 2006.
    • (2006) TPAMI
    • Constantinopoulos, C.1    Titsias, M.2    Likas, A.3
  • 36
    • 85015152103 scopus 로고    scopus 로고
    • Sparse multinomial logistic regression via Bayesian l1 regularisation
    • G. Cawley, N. Talbot, and M. Girolami, "Sparse multinomial logistic regression via bayesian l1 regularisation," in NIPS, 2006.
    • (2006) NIPS
    • Cawley, G.1    Talbot, N.2    Girolami, M.3
  • 38
    • 79959545846 scopus 로고    scopus 로고
    • Harnessing the crowdsourcing power of social media for disaster relief
    • H. Gao, G. Barbier, and R. Gollsby, "Harnessing the crowdsourcing power of social media for disaster relief," in IEEE Intelligent Systems, 2011.
    • (2011) IEEE Intelligent Systems
    • Gao, H.1    Barbier, G.2    Gollsby, R.3
  • 39
    • 74549114844 scopus 로고    scopus 로고
    • Exploiting internal and external semantics for the clustering of short texts using world knowledge
    • X. Hu, N. Sun, C. Zhang and T. Chua, "Exploiting internal and external semantics for the clustering of short texts using world knowledge," in CIKM, 2009.
    • (2009) CIKM
    • Hu, X.1    Sun, N.2    Zhang, C.3    Chua, T.4
  • 40
    • 78649930542 scopus 로고    scopus 로고
    • Coselection of features and instances for unsupervised rare category analysis
    • J. He and J. Carbonell, "Coselection of features and instances for unsupervised rare category analysis," in Statistical Analysis and Data Mining, 2010.
    • (2010) Statistical Analysis and Data Mining
    • He, J.1    Carbonell, J.2
  • 41
    • 77954603933 scopus 로고    scopus 로고
    • Modeling relationship strength in online social networks
    • R. Xiang, J. Neville, and M. Rogati, "Modeling relationship strength in online social networks," in WWW, 2010.
    • (2010) WWW
    • Xiang, R.1    Neville, J.2    Rogati, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.