메뉴 건너뛰기




Volumn 47, Issue 2, 2011, Pages 202-214

Exploiting probabilistic topic models to improve text categorization under class imbalance

Author keywords

Class imbalance; Noisy data; Probabilistic topic model; Rare class analysis; Text categorization

Indexed keywords

CLASS IMBALANCE; NOISY DATA; PROBABILISTIC TOPIC MODEL; RARE CLASS; TEXT CATEGORIZATION;

EID: 79951944700     PISSN: 03064573     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ipm.2010.07.003     Document Type: Article
Times cited : (45)

References (29)
  • 1
    • 27144531570 scopus 로고    scopus 로고
    • A study of the behavior of several methods for balancing machine learning training data
    • G.E.A.P.A. Batista, R.C. Prati, and M.C. Monard A study of the behavior of several methods for balancing machine learning training data SIGKDD Explorations Newsletter 6 1 2004 20 29
    • (2004) SIGKDD Explorations Newsletter , vol.6 , Issue.1 , pp. 20-29
    • Batista, G.E.A.P.A.1    Prati, R.C.2    Monard, M.C.3
  • 10
    • 0031710353 scopus 로고    scopus 로고
    • Webace: A web agent for document categorization and exploration
    • Han, E.-H.; Boley, D.; Gini, M.; Gross, R.; Hastings, K.; Karypis, G.; et al. (1998). Webace: A web agent for document categorization and exploration. In AGENTS '98 (pp. 408-415).
    • (1998) AGENTS , vol.98 , pp. 408-415
    • Han, E.-H.1    Boley, D.2    Gini, M.3    Gross, R.4    Hastings, K.5    Karypis, G.6
  • 12
    • 0005255842 scopus 로고    scopus 로고
    • The class imbalance problem: Significance and strategies
    • Japkowicz, N. (2000). The class imbalance problem: Significance and strategies. In IC-AI'2000 (Vol. 1, pp. 111-117).
    • (2000) IC-AI'2000 , vol.1 , pp. 111-117
    • Japkowicz, N.1
  • 13
    • 33845536164 scopus 로고    scopus 로고
    • The class imbalance problem: A systematic study
    • N. Japkowicz, and S. Stephen The class imbalance problem: A systematic study Intelligent Data Analysis 6 5 2002 429 449
    • (2002) Intelligent Data Analysis , vol.6 , Issue.5 , pp. 429-449
    • Japkowicz, N.1    Stephen, S.2
  • 15
    • 55949121544 scopus 로고    scopus 로고
    • Text classification from unlabeled documents with bootstrapping and feature projection techniques
    • Y. Ko, and J. Seo Text classification from unlabeled documents with bootstrapping and feature projection techniques Information Processing and Management 45 1 2009 70 83
    • (2009) Information Processing and Management , vol.45 , Issue.1 , pp. 70-83
    • Ko, Y.1    Seo, J.2
  • 16
    • 0001972236 scopus 로고    scopus 로고
    • Addressing the curse of imbalanced training sets: One-sided selection
    • Kubat, M.; Matwin, S. (1997). Addressing the curse of imbalanced training sets: One-sided selection. In ICML 1997 (pp. 179-186).
    • (1997) ICML 1997 , pp. 179-186
    • Kubat, M.1    Matwin, S.2
  • 17
    • 9444298027 scopus 로고    scopus 로고
    • Improving identification of difficult small classes by balancing class distribution
    • University of Tampere
    • Laurikkala, J. (2001). Improving identification of difficult small classes by balancing class distribution. Tech. Rep. A-2001-2, University of Tampere.
    • (2001) Tech. Rep. A-2001-2
    • Laurikkala, J.1
  • 19
    • 33750437739 scopus 로고    scopus 로고
    • Contextual feature selection for text classification
    • DOI 10.1016/j.ipm.2006.07.006, PII S0306457306001269
    • F. Paradis, and J.-Y. Nie Contextual feature selection for text classification Information Processing and Management 43 2 2007 344 352 (special issue on AIRS2005: Information Retrieval Research in Asia) (Pubitemid 44646716)
    • (2007) Information Processing and Management , vol.43 , Issue.2 , pp. 344-352
    • Paradis, F.1    Nie, J.-Y.2
  • 20
    • 0002442796 scopus 로고    scopus 로고
    • Machine learning in automated text categorization
    • F. Sebastiani Machine learning in automated text categorization ACM Computing Surveys 34 1 2002 1 47
    • (2002) ACM Computing Surveys , vol.34 , Issue.1 , pp. 1-47
    • Sebastiani, F.1
  • 22
    • 17844387127 scopus 로고    scopus 로고
    • Neighbor-weighted K-nearest neighbor for unbalanced text corpus
    • DOI 10.1016/j.eswa.2004.12.023, PII S0957417404001708
    • S. Tan Neighbor-weighted k-nearest neighbor for unbalanced text corpus Expert Systems with Applications 28 4 2005 667 671 (Pubitemid 40583844)
    • (2005) Expert Systems with Applications , vol.28 , Issue.4 , pp. 667-671
    • Tan, S.1
  • 25
    • 0015361129 scopus 로고
    • Asymptotic properties of nearest neighbor rules using edited data
    • D.L. Wilson Asymptotic properties of nearest neighbor rules using edited data IEEE Transactions on Systems, Man and Cybernetics 2 3 1972 408 421
    • (1972) IEEE Transactions on Systems, Man and Cybernetics , vol.2 , Issue.3 , pp. 408-421
    • Wilson, D.L.1
  • 27
    • 85024373635 scopus 로고    scopus 로고
    • A re-examination of text categorization methods
    • Yang, Y.; Liu, X. (1999). A re-examination of text categorization methods. In SIGIR '99 (pp. 42-49).
    • (1999) SIGIR '99 , pp. 42-49
    • Yang, Y.1    Liu, X.2
  • 28
    • 16644402628 scopus 로고    scopus 로고
    • Feature selection for text categorization on imbalanced data
    • Z. Zheng, X. Wu, and R. Srihari Feature selection for text categorization on imbalanced data SIGKDD Explorations Newsletter 6 1 2004 80 89
    • (2004) SIGKDD Explorations Newsletter , vol.6 , Issue.1 , pp. 80-89
    • Zheng, Z.1    Wu, X.2    Srihari, R.3
  • 29
    • 19544372918 scopus 로고    scopus 로고
    • Class noise vs. attribute noise: A quantitative study
    • X. Zhu, and X. Wu Class noise vs. attribute noise: A quantitative study Artificial Intelligence Review 22 3 2004 177 210
    • (2004) Artificial Intelligence Review , vol.22 , Issue.3 , pp. 177-210
    • Zhu, X.1    Wu, X.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.