A hybrid method for POI recommendation: combining check-in count, geographical information and reviews

Xiefeng Xu, Pengpeng Zhao*, Guanfeng Liu, Caidong Gu, Jiajie Xu, Jian Wu, Zhiming Cui

*Corresponding author for this work

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

Abstract

Due to the rapid development of mobile devices, global position systems (GPS),Web 2.0 and location-based social networks (LBSNs) have attracted millions of users to share their locations or experiences. Point of Interest (POI) recommendation plays an important role in exploring attractive locations. POI recommendation is associated with multi-dimensional factors, such as check-in counts, geographical influence, and review text. Although GeoMF can model geographical influence well by matrix factorization (MF), it ignores the impact of review text for POI recommendation. We propose a hybrid method to joint check-in counts, geographical information and reviews for POI recommendation. Specifically, we connect check-in counts and geographical information by incorporating geographical information into matrix factorization. In addition, we combine check-in counts with review text by aligning latent check-in counts in MF, and utilize hidden review topics obtained from LDA by a transformation. The results of our experiments on the real-world dataset show that our proposed model can improve the performance of recommendation.

Original languageEnglish
Title of host publicationWeb Technologies and Applications
Subtitle of host publication18th Asia-Pacific Web Conference, APWeb 2016, Proceedings, Part II
EditorsFeifei Li, Kyuseok Shim, Kai Zheng, Guanfeng Liu
Place of PublicationSwitzerland
PublisherSpringer, Springer Nature
Pages162-173
Number of pages12
Volume9932 LNCS
ISBN (Electronic)9783319458175
ISBN (Print)9783319458168
DOIs
Publication statusPublished - 2016
Externally publishedYes
EventAsia-Pacific Web Conference (18th : 2016) - Suzhou, China
Duration: 23 Sep 201625 Sep 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9932 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

ConferenceAsia-Pacific Web Conference (18th : 2016)
Abbreviated titleAPWeb 2016
CountryChina
CitySuzhou
Period23/09/1625/09/16

Keywords

  • Geographical information
  • POI recommendation
  • Reviews

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