Unsupervised Learning of Paragraph Embeddings for Context-Aware Recommendation

The sparsity of data is one of the main reasons restricting the performance of recommender systems. In order to solve the sparsity problem, some recommender systems use auxiliary information, especially text information, as a supplement to increase the prediction accuracy of the ratings. However, th...

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Bibliographic Details
Published in:IEEE access 2019, Vol.7, p.43100-43109
Main Authors: Xie, Jin, Zhu, Fuxi, Huang, Minxue, Xiong, Naixue, Huang, Sheng, Xiong, Wei
Format: Article
Language:English
Subjects:
Context
Context awareness
Context modeling
Data models
Deep learning
Factorization
Feature extraction
Mathematical analysis
Matrix algebra
Matrix methods
Ratings
Recommender systems
Semantics
Sparsity
text analysis
Unsupervised learning
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