Weighting of noun phrases based on local frequency of nouns

Yasuhiro Yamada, Yuusuke Himeno, Tetsuya Nakatoh

    研究成果: Chapter in Book/Report/Conference proceedingConference contribution

    2 被引用数 (Scopus)

    抄録

    The tf-idf is a well-known weighting measure for words in texts. It measures both the frequency and the locality of words. It is often used for information retrieval and text mining. However, a lot of infrequent words have the same tf-idf value. In this study, the words are noun phrases. This paper proposes a novel weighting measure for noun phrases in texts by using the local frequency of nouns that construct a noun phrase. The proposed measure is calculated by combining the tf-idf of a noun phrase and the average of the difference between its frequency and the frequency of nouns within the phrase. The proposed measure was evaluated in experiments on the datasets of 19,997 newsgroup texts written in English and 206 Wikipedia pages written in Japanese. The experiments showed that the number of noun phrases with the same proposed measure is less than the number of noun phrases with the same tf-idf.

    本文言語英語
    ホスト出版物のタイトルRecent Advances on Soft Computing and Data Mining - Proceedings of the 3rd International Conference on Soft Computing and Data Mining SCDM 2018
    編集者Jemal H. Abawajy, Rozaida Ghazali, Mustafa Mat Deris, Nazri Mohd Nawi
    出版社Springer Verlag
    ページ436-445
    ページ数10
    ISBN(印刷版)9783319725499
    DOI
    出版ステータス出版済み - 2018
    イベント3rd International Conference on Soft Computing and Data Mining, SCDM 2018 - Johor, マレーシア
    継続期間: 2 6 20182 8 2018

    出版物シリーズ

    名前Advances in Intelligent Systems and Computing
    700
    ISSN(印刷版)2194-5357

    その他

    その他3rd International Conference on Soft Computing and Data Mining, SCDM 2018
    国/地域マレーシア
    CityJohor
    Period2/6/182/8/18

    All Science Journal Classification (ASJC) codes

    • 制御およびシステム工学
    • コンピュータ サイエンス(全般)

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