492 citations · 1.2k across the 50 of their papers we have counts for
5 papers · 1 filter
Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation
Lianghao Xia, Chao Huang, Yong Xu +5
Accurate user and item embedding learning is crucial for modern recommender systems. However, most existing recommendation techniques have thus far focused on modeling users' prefe…
Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation
Yitong Pang, Lingfei Wu, Qi Shen +6
Predicting the next interaction of a short-term interaction session is a challenging task in session-based recommendation. Almost all existing works rely on item transition pattern…
Mining Implicit Relevance Feedback from User Behavior for Web Question Answering
Linjun Shou, Shining Bo, Feixiang Cheng +3
Training and refreshing a web-scale Question Answering (QA) system for a multi-lingual commercial search engine often requires a huge amount of training examples. One principled id…
Visually-aware Recommendation with Aesthetic Features
Wenhui Yu, Xiangnan He, Jian Pei +4
Visual information plays a critical role in human decision-making process. While recent developments on visually-aware recommender systems have taken the product image into account…
Online Visual Analytics of Text Streams
Shixia Liu, Jialun Yin, Xiting Wang +3
We present an online visual analytics approach to helping users explore and understand hierarchical topic evolution in high-volume text streams. The key idea behind this approach i…