Feature words that classify problem sentence in scientific article

Toshihiko Sakai, Sachio Hirokawa

    研究成果: 書籍/レポート タイプへの寄稿会議への寄与

    38 被引用数 (Scopus)

    抄録

    Literature review requires understanding the contents from several view points, such as the problem and the method that the articles describe. Search from these viewpoints will improve the efficiency of survey, if particular segments of articles were extracted, indexed and can be used as auxiliary query. This paper focuses on sentences that describe the problem in an abstract and the feature sets that classify such problem sentences. Classification performance are evaluated by 10-fold cross-validation for six candidate sets of feature words. It turned out that the set of all words gains the best performance if 90% of the data are used as training data. However, the set of a small number of words with positive scores outperforms other feature sets, if the training data is only 10%. In such a realistic situation, the feature words are effective in improving classification performance.

    本文言語英語
    ホスト出版物のタイトル14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012 - Proceedings
    ページ360-367
    ページ数8
    DOI
    出版ステータス出版済み - 2012
    イベント14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012 - Bali, インドネシア
    継続期間: 12月 3 201212月 5 2012

    その他

    その他14th International Conference on Information Integration and Web-Based Applications and Services, iiWAS 2012
    国/地域インドネシア
    CityBali
    Period12/3/1212/5/12

    !!!All Science Journal Classification (ASJC) codes

    • 人間とコンピュータの相互作用
    • コンピュータ ネットワークおよび通信
    • コンピュータ ビジョンおよびパターン認識
    • ソフトウェア

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