Disentangled Representation Learning for Recommendation

There exist complex interactions among a large number of latent factors behind the decision making processes of different individuals, which drive the various user behavior patterns in recommender systems. These factors hidden in those diverse behaviors demonstrate highly entangled patterns, coverin...

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Bibliographic Details
Published in:	IEEE transactions on pattern analysis and machine intelligence 2023-01, Vol.45 (1), p.408-424
Main Authors:	Wang, Xin, Chen, Hong, Zhou, Yuwei, Ma, Jianxin, Zhu, Wenwu
Format:	Article
Language:	English
Subjects:	Coders Controllability Data models Decision making Disentangled representation Entanglement Footwear Image color analysis Information theory Learning Mathematical models recommendation Recommender systems Representation learning Representations Robust control Semantics Visual signals Visualization
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