Personalized Neural Embeddings for Collaborative Filtering with Text

@inproceedings{Hu2019PersonalizedNE,
  title={Personalized Neural Embeddings for Collaborative Filtering with Text},
  author={Guangneng Hu},
  booktitle={NAACL},
  year={2019}
}
Collaborative filtering (CF) is a core technique for recommender systems. Traditional CF approaches exploit user-item relations (e.g., clicks, likes, and views) only and hence they suffer from the data sparsity issue. Items are usually associated with unstructured text such as article abstracts and product reviews. We develop a Personalized Neural Embedding (PNE) framework to exploit both interactions and words seamlessly. We learn such embeddings of users, items, and words jointly, and predict… Expand
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