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Volumn 21, Issue 3, 2009, Pages 428-442

Distributional features for text categorization

Author keywords

Distributional feature; Machine learning; Text categorization; Text mining; Tfidf

Indexed keywords

DISTRIBUTIONAL FEATURE; MACHINE LEARNING; TEXT CATEGORIZATION; TEXT MINING; TFIDF;

EID: 70350448587     PISSN: 10414347     EISSN: None     Source Type: Journal    
DOI: 10.1109/TKDE.2008.166     Document Type: Article
Times cited : (99)

References (36)
  • 1
    • 0032264186 scopus 로고    scopus 로고
    • Distributional clustering of words for text classification
    • L.D. BakerandA.K.McCallum, "Distributional Clustering of Words for Text Classification, " Proc. ACM SIGIR '98, pp. 96-103, 1998.
    • (1998) Proc. ACM SIGIR '98 , pp. 96-103
    • Bakerand, A.K.1    Mccallum, L.D.2
  • 2
    • 77951430107 scopus 로고    scopus 로고
    • Distributional word clusters versus words for text categorization
    • R. Bekkerman, R. El-Yaniv, N. Tishby, and Y. Winter, "Distributional Word Clusters versus Words for Text Categorization, " J. Machine Learning Research, vol. 3, pp. 1182-1208, 2003.
    • (2003) J. Machine Learning Research , vol.3 , pp. 1182-1208
    • Bekkerman, R.1    El-Yaniv, R.2    Tishby, N.3    Winter, Y.4
  • 4
    • 85029933081 scopus 로고
    • Passage retrieval evidence in document retrieval
    • J.P. Callan, "Passage Retrieval Evidence in Document Retrieval, " Proc. ACM SIGIR '94, pp. 302-310, 1994.
    • (1994) Proc. ACM SIGIR '94 , pp. 302-310
    • Callan, J.P.1
  • 5
    • 0242647875 scopus 로고    scopus 로고
    • A learner- independent evaluation of the usefulness of statistical phrases for automated text categorization
    • A.G. Chin, ed., Idea Group Publishing
    • M.F. Caropreso, S. Matwin, and F. Sebastiani, "A Learner- Independent Evaluation of the Usefulness of Statistical Phrases for Automated Text Categorization, " Text Databases and Document Management: Theory and Practice, A.G. Chin, ed., pp. 78-102, Idea Group Publishing, 2001.
    • (2001) Text Databases and Document Management: Theory and Practice , pp. 78-102
    • Caropreso, M.F.1    Matwin, S.2    Sebastiani, F.3
  • 8
    • 0031361611 scopus 로고    scopus 로고
    • Machine learning research: Four current directions
    • T.G. Dietterich, "Machine Learning Research: Four Current Directions, " AI Magazine, vol. 18, no. 4, pp. 97-136, 1997.
    • (1997) AI Magazine , vol.18 , Issue.4 , pp. 97-136
    • Dietterich, T.G.1
  • 13
    • 84957069814 scopus 로고    scopus 로고
    • Text categorization with support vector machines: Learning with many relevant features
    • T. Joachims, "Text Categorization with Support Vector Machines: Learning with Many Relevant Features, " Proc. 10th European Conf. Machine Learning (ECML '98), pp. 137-142, 1998.
    • (1998) Proc. 10th European Conf. Machine Learning (ECML '98) , pp. 137-142
    • Joachims, T.1
  • 14
    • 3042796461 scopus 로고    scopus 로고
    • An evaluation of passage-based text categorization
    • J. Kim and M.H. Kim, "An Evaluation of Passage-Based Text Categorization, " J. Intelligent Information Systems, vol. 23, no. 1, pp. 47-65, 2004.
    • (2004) J. Intelligent Information Systems , vol.23 , Issue.1 , pp. 47-65
    • Kim, J.1    Kim, M.H.2
  • 15
    • 0344927122 scopus 로고    scopus 로고
    • Improving text categorization using the importance of sentences
    • Y. Ko, J. Park, and J. Seo, "Improving Text Categorization Using the Importance of Sentences, " Information Processing and Management, vol. 40, no. 1, pp. 65-79, 2004.
    • (2004) Information Processing and Management , vol.40 , Issue.1 , pp. 65-79
    • Ko, Y.1    Park, J.2    Seo, J.3
  • 18
    • 0036161242 scopus 로고    scopus 로고
    • Text categorization with support vector machines: How to represent text in input space?
    • E. Leopold and J. Kingermann, "Text Categorization with Support Vector Machines: How to Represent Text in Input Space?" Machine Learning, vol. 46, nos. 1-3, pp. 423-444, 2002.
    • (2002) Machine Learning , vol.46 , Issue.1-3 , pp. 423-444
    • Leopold, E.1    Kingermann, J.2
  • 20
    • 0027001621 scopus 로고
    • An evaluation of phrasal and clustered representations on a text categorization task
    • D.D. Lewis, "An Evaluation of Phrasal and Clustered Representations on a Text Categorization Task, " Proc. ACM SIGIR '92, pp. 37-50, 1992.
    • (1992) Proc. ACM SIGIR '92 , pp. 37-50
    • Lewis, D.D.1
  • 21
    • 1942516915 scopus 로고    scopus 로고
    • A loss function analysis for classification methods in text categorization
    • F. Li and Y. Yang, "A Loss Function Analysis for Classification Methods in Text Categorization, " Proc. 20th Int'l Conf. Machine Learning (ICML '03), pp. 472-479, 2003.
    • (2003) Proc. 20th Int'l Conf. Machine Learning (ICML '03) , pp. 472-479
    • Li, F.1    Yang, Y.2
  • 23
  • 28
    • 0033905095 scopus 로고    scopus 로고
    • Boostexter: A boosting-based system for text categorization
    • R.E. Schapire and Y. Singer, "Boostexter: A Boosting-Based System for Text Categorization, " Machine Learning, vol. 39, nos. 2/3, pp. 135-168, 2000.
    • (2000) Machine Learning , vol.39 , Issue.2-3 , pp. 135-168
    • Schapire, R.E.1    Singer, Y.2
  • 30
    • 0002442796 scopus 로고    scopus 로고
    • Machine learning in automated text categorization
    • F. Sebastiani, "Machine Learning in Automated Text Categorization, " ACM Computing Surveys, vol. 34, no. 1, pp. 1-47, 2002.
    • (2002) ACM Computing Surveys , vol.34 , Issue.1 , pp. 1-47
    • Sebastiani, F.1
  • 34
    • 0034785186 scopus 로고    scopus 로고
    • A study on thresholding strategies for text categorization
    • Y. Yang, "A Study on Thresholding Strategies for Text Categorization, " Proc. ACM SIGIR '01, pp. 137-145, 2001.
    • (2001) Proc. ACM SIGIR '01 , pp. 137-145
    • Yang, Y.1
  • 35
    • 85024373635 scopus 로고    scopus 로고
    • A re-examination of text categorization methods
    • Y. Yang and X. Liu, "A Re-Examination of Text Categorization Methods, " Proc. ACM SIGIR '99, pp. 42-49, 1999.
    • (1999) Proc. ACM SIGIR '99 , pp. 42-49
    • Yang, Y.1    Liu, X.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.