1.5k citations · 6.3k across the 35 of their papers we have counts for
10 papers · 1 filter
Neural News Recommendation with Attentive Multi-View Learning
Chuhan Wu, Fangzhao Wu, Mingxiao An +3
Personalized news recommendation is very important for online news platforms to help users find interested news and improve user experience. News and user representation learning i…
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…
Personalized Multimedia Item and Key Frame Recommendation
Le Wu, Lei Chen, Yonghui Yang +4
When recommending or advertising items to users, an emerging trend is to present each multimedia item with a key frame image (e.g., the poster of a movie). As each multimedia item…
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…
Transcribing Content from Structural Images with Spotlight Mechanism
Yu Yin, Zhenya Huang, Enhong Chen +4
Transcribing content from structural images, e.g., writing notes from music scores, is a challenging task as not only the content objects should be recognized, but the internal str…
Neural Chinese Named Entity Recognition via CNN-LSTM-CRF and Joint Training with Word Segmentation
Fangzhao Wu, Junxin Liu, Chuhan Wu +2
Chinese named entity recognition (CNER) is an important task in Chinese natural language processing field. However, CNER is very challenging since Chinese entity names are highly c…
Neural Chinese Word Segmentation with Lexicon and Unlabeled Data via Posterior Regularization
Junxin Liu, Fangzhao Wu, Chuhan Wu +2
Existing methods for CWS usually rely on a large number of labeled sentences to train word segmentation models, which are expensive and time-consuming to annotate. Luckily, the unl…
Knowledge Graph Convolutional Networks for Recommender Systems
Hongwei Wang, Miao Zhao, Xing Xie +2
To alleviate sparsity and cold start problem of collaborative filtering based recommender systems, researchers and engineers usually collect attributes of users and items, and desi…
Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation
Hongwei Wang, Fuzheng Zhang, Miao Zhao +3
Collaborative filtering often suffers from sparsity and cold start problems in real recommendation scenarios, therefore, researchers and engineers usually use side information to a…