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Volumn 25, Issue 1, 2005, Pages 47-67

Automatic category theme identification and hierarchy generation for Chinese text categorization

Author keywords

Automatic category hierarchy generation; Automatic category theme identification; Self organizing maps; Text categorization; Text mining

Indexed keywords

DATA MINING; FORMAL LANGUAGES; HIERARCHICAL SYSTEMS; KNOWLEDGE BASED SYSTEMS; PROBLEM SOLVING;

EID: 23944513353     PISSN: 09259902     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10844-005-0859-6     Document Type: Article
Times cited : (4)

References (14)
  • 1
    • 0028461417 scopus 로고
    • Automated learning of decision rules for text categorization
    • Apte, C., Damerau, F., and Weiss, S.M. (1994). Automated Learning of Decision Rules for Text Categorization. ACM Trans. Information Systems, 12(3), 233-251.
    • (1994) ACM Trans. Information Systems , vol.12 , Issue.3 , pp. 233-251
    • Apte, C.1    Damerau, F.2    Weiss, S.M.3
  • 10
  • 12
    • 84880663504 scopus 로고    scopus 로고
    • The cluster-abstraction model: Unsupervised learning of topic hierarchies from text data
    • Hofmann, T. (1999). The Cluster-Abstraction Model: Unsupervised Learning of Topic Hierarchies from Text Data. In Proc. Int'l Joint Conf. on Artificial Intelligence (IJCAI 99) (pp. 682-687).
    • (1999) Proc. Int'l Joint Conf. on Artificial Intelligence (IJCAI 99) , pp. 682-687
    • Hofmann, T.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.