Modeling Periodic Pattern with Self-Attention Network for Sequential Recommendation

Jun Ma, Pengpeng Zhao, Yanchi Liu, Victor S. Sheng, Jiajie Xu, Lei Zhao

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

Abstract

Repeat consumption is a common phenomenon in sequential recommendation tasks, where a user revisits or repurchases items that (s)he has interacted before. Previous researches have paid attention to repeat recommendation and made great achievements in this field. However, existing studies rarely considered the phenomenon that the consumers tend to show different behavior periodicities on different items, which is important for recommendation performance. In this paper, we propose a holistic model, which integrates Graph Convolutional Network with Periodic-Attenuated Self-Attention Network (GPASAN) to model user’s different behavior patterns for a better recommendation. Specifically, we first process all the users’ action sequences to construct a graph structure, which captures the complex item connection and obtains item representations. Then, we employ a periodic channel and an attenuated channel that incorporate temporal information into the self-attention mechanism to model the user’s periodic and novel behaviors, respectively. Extensive experiments conducted on three public datasets show that our proposed model outperforms the state-of-the-art methods consistently.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 25th International Conference, DASFAA 2020, Proceedings
EditorsYunmook Nah, Bin Cui, Sang-Won Lee, Jeffrey Xu Yu, Yang-Sae Moon, Steven Euijong Whang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages557-572
Number of pages16
ISBN (Print)9783030594183
DOIs
StatePublished - 2020
Event25th International Conference on Database Systems for Advanced Applications, DASFAA 2020 - Jeju, Korea, Republic of
Duration: Sep 24 2020Sep 27 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12114 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference25th International Conference on Database Systems for Advanced Applications, DASFAA 2020
Country/TerritoryKorea, Republic of
CityJeju
Period09/24/2009/27/20

Keywords

  • Periodic pattern
  • Self-attention network
  • Sequential recommendation

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