S-Walk: Accurate and scalable session-based recommendation with randomwalks

Minjin Choi, Jinhong Kim, Joonseok Lee, Hyunjung Shim, Jongwuk Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

Session-based recommendation (SR) predicts the next items from a sequence of previous items consumed by an anonymous user. Most existing SR models focus only on modeling intra-session characteristics but pay less attention to inter-session relationships of items, which has the potential to improve accuracy. Another critical aspect of recommender systems is computational efficiency and scalability, considering practical feasibility in commercial applications. To account for both accuracy and scalability, we propose a novel session-based recommendation with a random walk, namely S-Walk. Precisely, S-Walk effectively captures intra- and inter-session correlations by handling high-order relationships among items using random walks with restart (RWR). By adopting linear models with closed-form solutions for transition and teleportation matrices that constitute RWR, S-Walk is highly efficient and scalable. Extensive experiments demonstrate that S-Walk achieves comparable or state-of-the-art performance in various metrics on four benchmark datasets. Moreover, the model learned by S-Walk can be highly compressed without sacrificing accuracy, conducting two or more orders of magnitude faster inference than existing DNN-based models, making it suitable for large-scale commercial systems.

Original languageEnglish
Title of host publicationWSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining
PublisherAssociation for Computing Machinery, Inc
Pages150-160
Number of pages11
ISBN (Electronic)9781450391320
DOIs
Publication statusPublished - 2022 Feb 11
Event15th ACM International Conference on Web Search and Data Mining, WSDM 2022 - Virtual, Online, United States
Duration: 2022 Feb 212022 Feb 25

Publication series

NameWSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining

Conference

Conference15th ACM International Conference on Web Search and Data Mining, WSDM 2022
Country/TerritoryUnited States
CityVirtual, Online
Period22/2/2122/2/25

Bibliographical note

Publisher Copyright:
© 2022 ACM.

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Computer Science Applications
  • Software

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