Personalized entity recommendation: A heterogeneous information network approach

Xiao Yu, Xiang Ren, Yizhou Sun, Quanquan Gu, Bradley Sturt, Urvashi Khandelwal, Brandon Norick, Jiawei Han

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

Abstract

Among different hybrid recommendation techniques, network-based entity recommendation methods, which utilize user or item relationship information, are beginning to attract increasing attention recently. Most of the previous studies in this category only consider a single relationship type, such as friendships in a social network. In many scenarios, the entity recommendation problem exists in a heterogeneous information network environment. Different types of relationships can be potentially used to improve the recommendation quality. In this paper, we study the entity recommendation problem in heterogeneous information networks. Specifically, we propose to combine heterogeneous relationship information for each user differently and aim to provide high-quality personalized recommendation results using user implicit feedback data and personalized recommendation models. In order to take full advantage of the relationship heterogeneity in information networks, we first introduce meta-path-based latent features to represent the connectivity between users and items along different types of paths. We then define recommendation models at both global and personalized levels and use Bayesian ranking optimization techniques to estimate the proposed models. Empirical studies show that our approaches outperform several widely employed or the state-of-the-art entity recommendation techniques.

Original languageEnglish (US)
Title of host publicationWSDM 2014 - Proceedings of the 7th ACM International Conference on Web Search and Data Mining
PublisherAssociation for Computing Machinery
Pages283-292
Number of pages10
ISBN (Print)9781450323512
DOIs
StatePublished - 2014
Event7th ACM International Conference on Web Search and Data Mining, WSDM 2014 - New York, NY, United States
Duration: Feb 24 2014Feb 28 2014

Publication series

NameWSDM 2014 - Proceedings of the 7th ACM International Conference on Web Search and Data Mining

Other

Other7th ACM International Conference on Web Search and Data Mining, WSDM 2014
CountryUnited States
CityNew York, NY
Period2/24/142/28/14

Keywords

  • hybrid recommender system
  • information network

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

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