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7 papers · 2 filters
Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling
Jiarui Qin, Kan Ren, Yuchen Fang +2
Sequential recommendation task aims to predict user preference over items in the future given user historical behaviors. The order of user behaviors implies that there are resource…
KRED: Knowledge-Aware Document Representation for News Recommendations
Danyang Liu, Jianxun Lian, Shiyin Wang +4
News articles usually contain knowledge entities such as celebrities or organizations. Important entities in articles carry key messages and help to understand the content in a mor…
NPA: Neural News Recommendation with Personalized Attention
Chuhan Wu, Fangzhao Wu, Mingxiao An +3
News recommendation is very important to help users find interested news and alleviate information overload. Different users usually have different interests and the same user may…
Neural Review Rating Prediction with Hierarchical Attentions and Latent Factors
Xianchen Wang, Hongtao Liu, Peiyi Wang +4
Text reviews can provide rich useful semantic information for modeling users and items, which can benefit rating prediction in recommendation. Different words and reviews may have…
NRPA: Neural Recommendation with Personalized Attention
Hongtao Liu, Fangzhao Wu, Wenjun Wang +4
Existing review-based recommendation methods usually use the same model to learn the representations of all users/items from reviews posted by users towards items. However, differe…
A Neural Influence Diffusion Model for Social Recommendation
Le Wu, Peijie Sun, Yanjie Fu +3
Precise user and item embedding learning is the key to building a successful recommender system. Traditionally, Collaborative Filtering(CF) provides a way to learn user and item em…