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Volumn 25, Issue 5, 2003, Pages 628-633

Automatic textual document categorization based on generalized instance sets and a matamodel

Author keywords

Instance based learning; Metamodel learning; Text classification

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS; OPTIMIZATION; TEXT PROCESSING;

EID: 0038633562     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2003.1195997     Document Type: Article
Times cited : (54)

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    • Knerr, S.1    Personnaz, L.2    Dreyfus, G.3
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    • Lam, L.1    Suen, C.2
  • 10
    • 0033905095 scopus 로고    scopus 로고
    • BoosTexter: A boosting-based system for text categorization
    • R. Schapire and Y. Singer, "BoosTexter: A Boosting-Based System for Text Categorization," Machine Learning, vol. 39, no. 213, pp. 135-168, 2000.
    • (2000) Machine Learning , vol.39 , Issue.213 , pp. 135-168
    • Schapire, R.1    Singer, Y.2
  • 12
    • 0012460006 scopus 로고    scopus 로고
    • Neural network agents for learning semantic text classification
    • S. Wermter, "Neural Network Agents for Learning Semantic Text Classification," Information Retrieval vol. 3, no. 2, pp. 87-103, 2000.
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    • Wermter, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.