Feature words of moves in scientific abstracts

Kiyota Hashimoto, Tasanawan Soonklang, Sachio Hirokawa

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

    Abstract

    Extraction of structure from texts is a key issue of text mining. The rhetorical structure of move in scientific articles is useful for assisting in the reading and writing. In this paper, we classify move structure in the abstract of research articles with a small number of characteristic words that determine five moves of including background (B), purpose(P), method(M), result(R) and discussion(D). Eleven measures were introduced and used to select features of moves. Exhaustive parameter search were conducted to get the optimal combination of measure and the number of features. We applied support vector machine and evaluated 10 fold cross validations. The accuracies with optimal feature selections are 0.9022, 0.8322, 0.8442, 0.8820 and 0.8354 for B, P, M, R and D, respectively. They are 10% better than the baseline performance that use all keywords. This study surprisedly found that the negative feature words play central role for prediction performance improvement.

    Original languageEnglish
    Title of host publicationProceedings - 2016 5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages144-149
    Number of pages6
    ISBN (Electronic)9781467389853
    DOIs
    Publication statusPublished - Aug 31 2016
    Event5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016 - Kumamoto, Japan
    Duration: Jul 10 2016Jul 14 2016

    Other

    Other5th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2016
    Country/TerritoryJapan
    CityKumamoto
    Period7/10/167/14/16

    All Science Journal Classification (ASJC) codes

    • Information Systems
    • Computer Networks and Communications
    • Computer Science Applications
    • Computer Vision and Pattern Recognition

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