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a10-1. 雑誌掲載論文 >
このアイテムの引用には次の識別子を使用してください:
http://hdl.handle.net/10119/13699
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| タイトル: | A Reliably Weighted Collaborative Filtering System |
| 著者: | Nguyen, Van-Doan
Huynh, Van-Nam |
| キーワード: | Recommender Systems
Collaborative Filtering
Dempster-Shafer theory |
| 発行日: | 2015-07-12 |
| 出版者: | Springer |
| 誌名: | Lecture Notes in Computer Science |
| 巻: | 9161 |
| 開始ページ: | 429 |
| 終了ページ: | 439 |
| DOI: | 10.1007/978-3-319-20807-7_39 |
| 抄録: | In this paper, we develop a reliably weighted collaborative filtering system that first tries to predict all unprovided rating data by employing context information, and then exploits both predicted and provided rating data for generating suitable recommendations. Since the predicted rating data are not a hundred percent accurate, they are weighted weaker than the provided rating data when integrating both these kinds of rating data into the recommendation process. In order to flexibly represent rating data, Dempster-Shafer (DS) theory is used for data modelling in the system. The experimental results indicate that assigning weights to rating data is capable of improving the performance of the system. |
| Rights: | This is the author-created version of Springer, Van-Doan Nguyen, Van-Nam Huynh, Lecture Notes in Computer Science, 9161, 2015, 429-439. The original publication is available at www.springerlink.com, http://dx.doi.org/10.1007/978-3-319-20807-7_39 |
| URI: | http://hdl.handle.net/10119/13699 |
| 資料タイプ: | author |
| 出現コレクション: | a10-1. 雑誌掲載論文 (Journal Articles)
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このアイテムのファイル:
| ファイル |
記述 |
サイズ | 形式 |
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| 21940.pdf | | 515Kb | Adobe PDF | 見る/開く |
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