Embedded learning for leveraging multi-aspect in rating prediction of personalized recommendation
Collaborative filtering that relies on overall ratings has been widely accepted due to the ability to generate satisfactory recommendations. However, the most challenging difficulty of this approach is the lack of sufficient ratings or the so-called data sparsity. Moreover, sometimes these ratings a...
| 主要な著者: | , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Faculty of Computer Science and Information Technology, University of Malaya
2018
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| オンライン･アクセス: | http://psasir.upm.edu.my/id/eprint/72552/1/Embedded%20learning%20for%20leveraging%20multi-aspect%20in%20rating%20prediction%20of%20personalized%20recommendation.pdf |