カテゴリ: 論文誌(論文単位)グループ名: 【C】電子・情報・システム部門発行日: 2020/08/01タイトル(英語): A Method for Determining Web News Suitable as Teaching Materials of Regional Study in Elementary Schools著者名: Shinya Seki (Graduate School of Engineering, Kagawa University), Kazuaki Ando (Faculty of Engineering and Design, Kagawa University)著者名(英語): Shinya Seki (Graduate School of Engineering, Kagawa University), Kazuaki Ando (Faculty of Engineering and Design, Kagawa University)キーワード: newspaper in education，web news，support vector machine，elementary school teacher，news recommendation，NIE worksheet要約(英語): Newspaper in Education (NIE) is an educational approach to utilize the newspaper as a teaching material. The purpose of our research is to support elementary school teachers by recommending Web news suitable for regional study in NIE for elementary schools. This paper analyzes news articles within NIE worksheets and proposes a method to determine news articles suitable as teaching materials for regional study using Support Vector Machine (SVM) based on features of the contents of news articles, regionality and readability of articles. The effectiveness of the proposed method was evaluated by the experiments. From the experimental results, we confirmed that the proposed method using Word2Vec, Learned Kanji and Local Characteristic Words as the features obtained the highest precision of 87.6%. We also confirmed that there is a possibility that the proposed method can be applied to news articles in any region.本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.140 No.8 （2020） 特集Ⅰ：社会課題解決に向けた超スマート社会実現技術 特集Ⅱ：国際会議ICESS 2019本誌掲載ページ: 964-970 p原稿種別: 論文／英語電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/140/8/140_964/_article/-char/ja/
