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Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction
Haozhe Wu, Zhiyuan Hu, Jia Jia +3
Online Social Networks (OSNs) evolve through two pervasive behaviors: follow and unfollow, which respectively signify relationship creation and relationship dissolution. Researches…
Improving Neural Relation Extraction with Implicit Mutual Relations
Jun Kuang, Yixin Cao, Jianbing Zheng +3
Relation extraction (RE) aims at extracting the relation between two entities from the text corpora. It is a crucial task for Knowledge Graph (KG) construction. Most existing metho…
Modeling Embedding Dimension Correlations via Convolutional Neural Collaborative Filtering
Xiaoyu Du, Xiangnan He, Fajie Yuan +3
As the core of recommender system, collaborative filtering (CF) models the affinity between a user and an item from historical user-item interactions, such as clicks, purchases, an…
KGAT: Knowledge Graph Attention Network for Recommendation
Xiang Wang, Xiangnan He, Yixin Cao +2
To provide more accurate, diverse, and explainable recommendation, it is compulsory to go beyond modeling user-item interactions and take side information into account. Traditional…
Learning to Compose and Reason with Language Tree Structures for Visual Grounding
Richang Hong, Daqing Liu, Xiaoyu Mo +2
Grounding natural language in images, such as localizing "the black dog on the left of the tree", is one of the core problems in artificial intelligence, as it needs to comprehend…
Future Data Helps Training: Modeling Future Contexts for Session-based Recommendation
Fajie Yuan, Xiangnan He, Haochuan Jiang +4
Session-based recommender systems have attracted much attention recently. To capture the sequential dependencies, existing methods resort either to data augmentation techniques or…