Predicting POI visits with a heterogeneous information network

Zih Syuan Wang, Jing Fu Juang, Wei Guang Teng

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

7 Citations (Scopus)

Abstract

A point of interest (POI) is a specific location that people may find useful or interesting. Examples include restaurants, stores, attractions, and hotels. With recent proliferation of location-based social networks (LBSNs), numerous users are gathered to share information on various POIs and to interact with each other. POI recommendation is then a crucial issue because it not only helps users to explore potential places but also gives LBSN providers a chance to post POI advertisements. As we utilize a heterogeneous information network to represent a LBSN in this work, POI recommendation is remodeled as a link prediction problem, which is significant in the field of social network analysis. Moreover, we propose to utilize the meta-path-based approach to extract implicit (but potentially useful) relationships between a user and a POI. Then, the extracted topological features are used to construct a prediction model with appropriate data classification techniques. In our experimental studies, the Yelp dataset is utilized as our testbed for performance evaluation purposes. Results of the experiments show that our prediction model is of good prediction quality in practical applications.

Original languageEnglish
Title of host publicationTAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages388-395
Number of pages8
ISBN (Electronic)9781467396066
DOIs
Publication statusPublished - 2016 Feb 12
EventConference on Technologies and Applications of Artificial Intelligence, TAAI 2015 - Tainan, Taiwan
Duration: 2015 Nov 202015 Nov 22

Publication series

NameTAAI 2015 - 2015 Conference on Technologies and Applications of Artificial Intelligence

Other

OtherConference on Technologies and Applications of Artificial Intelligence, TAAI 2015
CountryTaiwan
CityTainan
Period15-11-2015-11-22

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications

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