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dc.contributor.author 角田, 雅照 ja
dc.contributor.author 秋永, 知宏 ja
dc.contributor.author 引地, 一将 ja
dc.contributor.author 大杉, 直樹 ja
dc.contributor.author 柿元, 健 ja
dc.contributor.author 門田, 暁人 ja
dc.contributor.author 松本, 健一 ja
dc.date.accessioned 2018-11-22T05:25:41Z en
dc.date.available 2018-11-22T05:25:41Z en
dc.date.issued 2010 en
dc.identifier.issn 1341-4135 en
dc.identifier.uri http://hdl.handle.net/10061/12813 en
dc.description.abstract It is important for software engineers to improve their skills by self-learning existing software development techniques. However, it is not easy for engineers to find out which techniques should be learned because there are so many existing techniques and also new techniques are emerging continuously. To support software engineers’ self-learning, we propose a development technique recommendation method using collaborative filtering (CF). In our method, a user (engineer) gives ratings to development techniques based on his/her interest or benefit, then development techniques are recommended based on similarity measure of CF. The similarity is computed based on co-occurrence of terms of development techniques on web pages. We conducted an experiment to evaluate the recommendation accuracy of the proposed method. As a result, the average NDPM was 0.41 for recommending development techniques that are unfamiliar to software engineers. ja
dc.language.iso ja en
dc.publisher 教育システム情報学会 ja
dc.rights © 2010 教育システム情報学会 ja
dc.subject 学習支援 ja
dc.subject 協調フィルタリング ja
dc.subject クローリング ja
dc.subject 共起関係 ja
dc.title 協調フィルタリングを用いたソフトウェア技術者向け開発技術推薦の試み ja
dc.title.alternative A Development Technique Recommendation Method for Software Engineers Using Collaborative Filtering en
dc.type.nii Journal Article en
dc.title.transcription キョウチョウ フィルタリング ヲ モチイタ ソフトウェア ギジュツシャ ムケ カイハツ ギジュツ スイセン ノ ココロミ ja
dc.contributor.transcription マツモト, ケンイチ ja
dc.contributor.alternative Matsumoto, Kenichi en
dc.textversion publisher en
dc.identifier.ncid AN10474042 en
dc.identifier.jtitle 教育システム情報学会誌 ja
dc.identifier.volume 27 en
dc.identifier.issue 4 en
dc.identifier.spage 316 en
dc.identifier.epage 326 en
dc.relation.doi 10.14926/jsise.27.316 en
dc.identifier.NAIST-ID 73292310 en

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