Deriving an effective hypergraph model for point of interest recommendation

Meng Qi, Xin Li*, Lejian Liao, Dandan Song, Kwok Wai CHEUNG

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

1 Citation (Scopus)

Abstract

Point of interest (POI) recommendation on Location Based Social Networks (LBSN) is challenging as the data available for predicting the next point of interest is highly sparse. Addressing the sparsity issue becomes one of the keys to achieve accurate POI recommendation. A promising approach is to explore various types of relevant information carried by the network, e.g, network structures, spatial-temporal information and relations. In this paper, we put forward a hypergraph model to incorporate the higher-order relations of LBSNs for POI recommendation. Accordingly, we propose a hypergraph random walk (HRW) to be applied to such a complex hypergraph. The steady state distribution gives our derived recommendation on venues for each user. Experiments based on a real data set collected from Foursquare have been conducted to evaluate the efficiency and effectiveness of our proposed model with promising results obtained.

Original languageEnglish
Title of host publicationKnowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings
EditorsZili Zhang, Songmao Zhang, Zili Zhang, Martin Wirsing, Martin Wirsing, Martin Wirsing, Zili Zhang, Songmao Zhang, Songmao Zhang
PublisherSpringer Verlag
Pages771-777
Number of pages7
ISBN (Print)9783319251585, 9783319251585, 9783319251585
DOIs
Publication statusPublished - 2015
Event8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015 - Chongqing, China
Duration: 28 Oct 201530 Oct 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9403
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015
Country/TerritoryChina
CityChongqing
Period28/10/1530/10/15

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Hypergraph learning
  • POI recommendation

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