Modeling heterogeneous influences for point-of-interest recommendation in location-based social networks

Qing Guo, Zhu Sun, Jie Zhang, Yin-Leng Theng

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

Abstract

The huge amount of heterogeneous information in location-based social networks (LBSNs) creates great challenges for POI recommendation. User check-in behavior exhibits two properties, diversity and imbalance. To effectively model both properties, we propose an Aspect-aware Geo-Social Matrix Factorization (AGS-MF) approach to exploit various factors in a unified manner for more effective POI recommendation. Specifically, we first construct a novel knowledge graph (KG), named as Aspect-aware Geo-Social Influence Graph (AGS-IG), to unify multiple influential factors by integrating the heterogeneous information about users, POIs and aspects from reviews. We design an efficient meta-path based random walk to discover relevant neighbors of each user and POI based on multiple influential factors. The extracted neighbors are further incorporated into AGS-MF with automatically learned personalized weights for each user and POI. By doing so, both diversity and imbalance can be modeled for better capturing the characteristics of users and POIs. Experimental results on several real-world datasets demonstrate that AGS-MF outperforms state-of-the-art methods.
Original languageEnglish
Title of host publicationWeb Engineering
Subtitle of host publication19th International Conference, ICWE 2019, Proceedings
EditorsMaxim Bakaev, Flavius Frasincar, In-Young Ko
Place of PublicationSwitzerland
PublisherSpringer
Pages72-80
Number of pages9
ISBN (Electronic)9783030192747
ISBN (Print)9783030192730
DOIs
Publication statusPublished - 2019
Externally publishedYes
Event19th International Conference on Web Engineering, ICWE 2019 - Daejeon, Korea, Republic of
Duration: 11 Jun 201914 Jun 2019

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume11496
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference19th International Conference on Web Engineering, ICWE 2019
CountryKorea, Republic of
CityDaejeon
Period11/06/1914/06/19

Keywords

  • Location-based social network
  • POI recommendation
  • Knowledge graph
  • Matrix factorization

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