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融合元数据及 attention 机制的深度联合学习推荐.
融合元数据及 attention 机制的深度联合学习推荐.
- Source :
-
Application Research of Computers / Jisuanji Yingyong Yanjiu . Nov2019, Vol. 36 Issue 11, p3290-3293. 4p. - Publication Year :
- 2019
-
Abstract
- Most of the existing modeling methods of combining metadata are based on the same user I item attribute weights, so that the key relationships between users and items are not significant, and it is difficult to obtain better recommendation performance. To solve the above problems, this paper proposed a method of deep joint learning recommendation based on metadata and attention mechanism. It used double deep network joint learning, one of the networks implemented matrix nonlinear decomposition based on implicit feedback data to learn user/ project personalization relationship, and another network automatically captured influence the user/ item key attributes to recommend by using attention mechanism, through the user preference relation with weighted of different attributes modeling highlighted the extended model. Experimental results show that the proposed recommendation algorithm has better recommendation performance on two public datasets of MovieLens 100K and MovieLens lM. [ABSTRACT FROM AUTHOR]
Details
- Language :
- Chinese
- ISSN :
- 10013695
- Volume :
- 36
- Issue :
- 11
- Database :
- Academic Search Index
- Journal :
- Application Research of Computers / Jisuanji Yingyong Yanjiu
- Publication Type :
- Academic Journal
- Accession number :
- 140238902
- Full Text :
- https://doi.org/10.19734/j.issn.1001-3695.2018.04.0285