Multiplex Behavioral Relation Learning for Recommendation via Memory Augmented Transformer Network

Lianghao Xia
Lianghao Xia
Peng Dai
Peng Dai
Bo Zhang
Bo Zhang

SIGIR '20: The 43rd International ACM SIGIR conference on research and development in Information Retrieval Virtual Event China July, 2020, pp. 2397-2406, 2020.

Cited by: 0|Bibtex|Views70|DOI:https://doi.org/10.1145/3397271.3401445
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Other Links: dl.acm.org|dblp.uni-trier.de|academic.microsoft.com

Abstract:

Capturing users' precise preferences is of great importance in various recommender systems (e.g., e-commerce platforms and online advertising sites), which is the basis of how to present personalized interesting product lists to individual users. In spite of significant progress has been made to consider relations between users and items,...More

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