메뉴 건너뛰기




Volumn , Issue , 2008, Pages 713-721

Building semantic kernels for text classification using wikipedia

Author keywords

Kernel methods; Semantic kernels; Text classification; Wikipedia

Indexed keywords

BACKGROUND KNOWLEDGE; BAG OF WORDS; BOW APPROACHES; CLASSIFICATION ACCURACIES; CLASSIFICATION ALGORITHMS; DOCUMENT CLASSIFICATIONS; DOCUMENT REPRESENTATIONS; EMPIRICAL EVALUATIONS; HIGH DIMENSIONALITIES; KERNEL METHODS; NATURAL LANGUAGES; PREDICTION CAPABILITIES; REAL DATA SETS; SEMANTIC INFORMATIONS; TEXT CLASSIFICATION; TEXT DATUM; WIKIPEDIA;

EID: 65449130494     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1401890.1401976     Document Type: Conference Paper
Times cited : (185)

References (23)
  • 5
    • 9444244198 scopus 로고    scopus 로고
    • Mining the peanut gallery: Opinion extraction and semantic classification of product reviews
    • Budapest, Hungary
    • K. Dave, S. Lawrence, and D. M. Pennock. Mining the peanut gallery: Opinion extraction and semantic classification of product reviews. In International World Wide Web Conference, Budapest, Hungary, 2003.
    • (2003) International World Wide Web Conference
    • Dave, K.1    Lawrence, S.2    Pennock, D.M.3
  • 9
    • 33750719969 scopus 로고    scopus 로고
    • Overcoming the brittleness bottleneck using wikipedia: Enhancing text categorization with encyclopedic knowledge
    • Boston, Massachusetts
    • E. Gabrilovich and S. Markovitch. Overcoming the brittleness bottleneck using wikipedia: enhancing text categorization with encyclopedic knowledge. In National Conference on Artificial Intelligence (AAAI), Boston, Massachusetts, 2006.
    • (2006) National Conference on Artificial Intelligence (AAAI)
    • Gabrilovich, E.1    Markovitch, S.2
  • 13
    • 0000636553 scopus 로고    scopus 로고
    • Text categorization with support vector machines: Learning with many relevant features
    • Chemnitz, Germany, Springer
    • T. Joachims. Text categorization with support vector machines: Learning with many relevant features. In European Conference on Machine Learning, Chemnitz, Germany, 1998. Springer.
    • (1998) European Conference on Machine Learning
    • Joachims, T.1
  • 14
    • 85142688646 scopus 로고
    • Newsweeder: Learning to filter netnews
    • Tahoe City, California, Morgan Kaufmann
    • K. Lang. Newsweeder: Learning to filter netnews. In International Conference on Machine Learning, Tahoe City, California, 1995. Morgan Kaufmann.
    • (1995) International Conference on Machine Learning
    • Lang, K.1
  • 22
    • 85014894392 scopus 로고    scopus 로고
    • S. K. M. Wong, W. Ziarko, and P. C. N. Wong. Generalized vector space model in information retrieval. In ACM SIGIR Conference on Research and Development in Information Retrieval, pages 18-25, Montreal, Canada, 1985.
    • S. K. M. Wong, W. Ziarko, and P. C. N. Wong. Generalized vector space model in information retrieval. In ACM SIGIR Conference on Research and Development in Information Retrieval, pages 18-25, Montreal, Canada, 1985.
  • 23
    • 0003141935 scopus 로고    scopus 로고
    • A comparative study on feature selection in text categorization
    • Nashville, Tennessee, Morgan Kaufmann
    • Y. Yang and J. Pedersen. A comparative study on feature selection in text categorization. In International Conference on Machine Learning, Nashville, Tennessee, 1997. Morgan Kaufmann.
    • (1997) International Conference on Machine Learning
    • Yang, Y.1    Pedersen, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.