Personalized location recommendation on location-based social networks

Huiji Gao; Jiliang Tang; Huan Liu

doi:10.1145/2645710.2645776

Personalized location recommendation on location-based social networks

Huiji Gao, Jiliang Tang, Huan Liu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

14 Scopus citations

Abstract

Personalized location recommendation is a special topic of recommendation. It is related to human mobile behavior in the real world regarding various contexts including spatial, temporal, social, and content. The development of this topic is subject to the availability of human mobile data. The recent rapid growth of location-based social networks has alleviated such limitation, which promotes the development of various location recommendation techniques. This tutorial offers an overview, in a data mining perspective, of personalized location recommendation on locationbased social networks. It introduces basic concepts, summarizes unique LBSN characteristics and research opportunities, elaborates associated challenges, reviews state-ofthe- art algorithms with illustrative examples and real-world LBSN datasets, and discusses effective evaluation methods.

Original language	English (US)
Title of host publication	RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems
Publisher	Association for Computing Machinery
Pages	399-400
Number of pages	2
ISBN (Electronic)	9781450326681
DOIs	https://doi.org/10.1145/2645710.2645776
State	Published - Oct 6 2014
Event	8th ACM Conference on Recommender Systems, RecSys 2014 - Foster City, United States Duration: Oct 6 2014 → Oct 10 2014

Publication series

Name	RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems

Conference

Conference	8th ACM Conference on Recommender Systems, RecSys 2014
Country/Territory	United States
City	Foster City
Period	10/6/14 → 10/10/14

Keywords

Location recommendation
Location-based social networks
Personalization

ASJC Scopus subject areas

Computer Science Applications
Information Systems

Access to Document

10.1145/2645710.2645776

Cite this

Personalized location recommendation on location-based social networks. / Gao, Huiji; Tang, Jiliang; Liu, Huan.
RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems. Association for Computing Machinery, 2014. p. 399-400 (RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Gao, H, Tang, J & Liu, H 2014, Personalized location recommendation on location-based social networks. in RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems. RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems, Association for Computing Machinery, pp. 399-400, 8th ACM Conference on Recommender Systems, RecSys 2014, Foster City, United States, 10/6/14. https://doi.org/10.1145/2645710.2645776

@inproceedings{42c1a40a5e5c45c392276ff504e1702a,

title = "Personalized location recommendation on location-based social networks",

abstract = "Personalized location recommendation is a special topic of recommendation. It is related to human mobile behavior in the real world regarding various contexts including spatial, temporal, social, and content. The development of this topic is subject to the availability of human mobile data. The recent rapid growth of location-based social networks has alleviated such limitation, which promotes the development of various location recommendation techniques. This tutorial offers an overview, in a data mining perspective, of personalized location recommendation on locationbased social networks. It introduces basic concepts, summarizes unique LBSN characteristics and research opportunities, elaborates associated challenges, reviews state-ofthe- art algorithms with illustrative examples and real-world LBSN datasets, and discusses effective evaluation methods.",

keywords = "Location recommendation, Location-based social networks, Personalization",

author = "Huiji Gao and Jiliang Tang and Huan Liu",

note = "Publisher Copyright: Copyright {\textcopyright} 2014 ACM.; 8th ACM Conference on Recommender Systems, RecSys 2014 ; Conference date: 06-10-2014 Through 10-10-2014",

year = "2014",

month = oct,

day = "6",

doi = "10.1145/2645710.2645776",

language = "English (US)",

series = "RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems",

publisher = "Association for Computing Machinery",

pages = "399--400",

booktitle = "RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems",

}

TY - GEN

T1 - Personalized location recommendation on location-based social networks

AU - Gao, Huiji

AU - Tang, Jiliang

AU - Liu, Huan

PY - 2014/10/6

Y1 - 2014/10/6

N2 - Personalized location recommendation is a special topic of recommendation. It is related to human mobile behavior in the real world regarding various contexts including spatial, temporal, social, and content. The development of this topic is subject to the availability of human mobile data. The recent rapid growth of location-based social networks has alleviated such limitation, which promotes the development of various location recommendation techniques. This tutorial offers an overview, in a data mining perspective, of personalized location recommendation on locationbased social networks. It introduces basic concepts, summarizes unique LBSN characteristics and research opportunities, elaborates associated challenges, reviews state-ofthe- art algorithms with illustrative examples and real-world LBSN datasets, and discusses effective evaluation methods.

AB - Personalized location recommendation is a special topic of recommendation. It is related to human mobile behavior in the real world regarding various contexts including spatial, temporal, social, and content. The development of this topic is subject to the availability of human mobile data. The recent rapid growth of location-based social networks has alleviated such limitation, which promotes the development of various location recommendation techniques. This tutorial offers an overview, in a data mining perspective, of personalized location recommendation on locationbased social networks. It introduces basic concepts, summarizes unique LBSN characteristics and research opportunities, elaborates associated challenges, reviews state-ofthe- art algorithms with illustrative examples and real-world LBSN datasets, and discusses effective evaluation methods.

KW - Location recommendation

KW - Location-based social networks

KW - Personalization

UR - http://www.scopus.com/inward/record.url?scp=84908889814&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84908889814&partnerID=8YFLogxK

U2 - 10.1145/2645710.2645776

DO - 10.1145/2645710.2645776

M3 - Conference contribution

AN - SCOPUS:84908889814

T3 - RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems

SP - 399

EP - 400

BT - RecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems

PB - Association for Computing Machinery

T2 - 8th ACM Conference on Recommender Systems, RecSys 2014

Y2 - 6 October 2014 through 10 October 2014

ER -

Personalized location recommendation on location-based social networks

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this