An evidential reasoning based LSA approach to document classification for knowledge acquisition

R. Mohamed, J. Watada

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    5 Citations (Scopus)

    Abstract

    Web is one of major information sources. Failure in proper management of knowledge leads to incorrect results returned by search engines. Therefore, the web should have an effective information retrieval system to improve the correctness of retrieval results. This study provides a method to assign a new document to the fittest category out of predefined categories, where latent semantic analysis (LSA) is used to evaluate each term in documents, the similarity between terms and documents as well as the one between terms and categories. The objective of our method is to fuse evidential reasoning method with LSA which can assign a new document to a predefined category. The method provides better results in performance of classification comparing to the fusion of an evidential reasoning approach with term frequency inverse document frequency (TFIDF).

    Original languageEnglish
    Title of host publicationIEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management
    Pages1092-1096
    Number of pages5
    DOIs
    Publication statusPublished - 2010
    EventIEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010 - Macao
    Duration: 2010 Dec 72010 Dec 10

    Other

    OtherIEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010
    CityMacao
    Period10/12/710/12/10

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    Keywords

    • Categorization
    • Evidential reasoning
    • Knowledge management
    • Latent semantic analysis (LSA)

    ASJC Scopus subject areas

    • Industrial and Manufacturing Engineering

    Cite this

    Mohamed, R., & Watada, J. (2010). An evidential reasoning based LSA approach to document classification for knowledge acquisition. In IEEM2010 - IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1092-1096). [5674188] https://doi.org/10.1109/IEEM.2010.5674188