Unified collaborative filtering over graph embeddings

Pengfei Wang, Hanxiong Chen, Yadong Zhu, Huawei Shen, Yongfeng Zhang

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

14 Scopus citations

Abstract

Collaborative Filtering (CF) by learning from the wisdom of crowds has become one of the most important approaches to recommender systems research, and various CF models have been designed and applied to different scenarios. However, a challenging task is how to select the most appropriate CF model for a specific recommendation task. In this paper, we propose a Unified Collaborative Filtering framework based on Graph Embeddings (UGrec for short) to solve the problem. Specifically, UGrec models user and item interactions within a graph network, and sequential recommendation path is designed as a basic unit to capture the correlations between users and items. Mathematically, we show that many representative recommendation approaches and their variants can be mapped as a recommendation path in the graph. In addition, by applying a carefully designed attention mechanism on the recommendation paths, UGrec can determine the significance of each sequential recommendation path so as to conduct automatic model selection. Compared with state-of-the-art methods, our method shows significant improvements for recommendation quality. This work also leads to a deeper understanding of the connection between graph embeddings and recommendation algorithms.

Original languageEnglish (US)
Title of host publicationSIGIR 2019 - Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery, Inc
Pages155-164
Number of pages10
ISBN (Electronic)9781450361729
DOIs
StatePublished - Jul 18 2019
Event42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019 - Paris, France
Duration: Jul 21 2019Jul 25 2019

Publication series

NameSIGIR 2019 - Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval

Conference

Conference42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019
Country/TerritoryFrance
CityParis
Period7/21/197/25/19

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Applied Mathematics
  • Software

Keywords

  • Attention Mechanism
  • Collaborative Filtering
  • Model Selection
  • Recommender Systems
  • Sequential Recommendation Path

Fingerprint

Dive into the research topics of 'Unified collaborative filtering over graph embeddings'. Together they form a unique fingerprint.

Cite this