Tag-Aware Personalized Recommendation Using a Deep-Semantic Similarity Model with Negative Sampling
With the rapid growth of social tagging systems, many efforts have been put on tag-aware personalized recommendation. However, due to uncontrolled vocabularies, social tags are usually redundant, sparse, and ambiguous. In this paper, we propose a deep neural network approach to solve this problem by...
| Główni autorzy: | , , , , |
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| Format: | Conference item |
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Association for Computing Machinery
2016
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