MGCN4REC: Multi-graph Convolutional Network for Next Basket Recommendation with Instant Interest

Yan Zhang, Bin Guo, Qianru Wang, Yueqi Sun, Zhiwen Yu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Sequential patterns involved in users’ historical behaviors have received extensive attention in recommendation system, which is important to represent item-level preferences. The existing works often combine the long-and short-term patterns to capture user’s preferences. But the short-term preferences modeled by the recent behavior patterns cannot clearly indicate the users’ instant interest. In this paper, we propose a sequential recommendation model MGCN4REC based on multi-graph to learn the representation of users and items and then model preferences and instant interests simultaneously. Firstly, this paper utilizes multi-graph convolutional network (MGCN) to learn users and items embeddings from multi-graph. Secondly, to aggregate preferences and instant interests, we use the attention mechanism to find the degrees of dependencies on these two features. Finally, this paper conducts experiments on real data sets of Amazon to evaluate the performance of MGCN4REC model, and the results show that our model outperforms the current state-of-the-art sequential recommendation methods over 15% on the metrics.

Original languageEnglish
Title of host publicationGreen, Pervasive, and Cloud Computing - 15th International Conference, GPC 2020, Proceedings
EditorsZhiwen Yu, Christian Becker, Guoliang Xing
PublisherSpringer Science and Business Media Deutschland GmbH
Pages171-185
Number of pages15
ISBN (Print)9783030642426
DOIs
StatePublished - 2020
Event15th International Conference on Green, Pervasive, and Cloud Computing, GPC 2020 - Xi'an, China
Duration: 13 Nov 202015 Nov 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12398 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Green, Pervasive, and Cloud Computing, GPC 2020
Country/TerritoryChina
CityXi'an
Period13/11/2015/11/20

Keywords

  • Attention mechanism
  • Instant interest
  • Multi-graph convolution network
  • Sequential recommendation

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