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Point-of-interest recommendations in location-based social networks

Published: 11 January 2016 Publication History

Abstract

Location-based social networks (LBSNs), e.g., Foursquare, Gowalla and Yelp, bridge the physical world with the virtual online world. LBSNs have accumulated plenty of community-contributed data such as social links between users, check-ins of users on points-of-interest (POIs), geographical information and categories of POIs, which reflect the preferences of users to POIs. Recommending users with their preferred POIs benefits people to explore new places and businesses to discover potential customers. This paper aims to recommend personalized POIs for users based on their preferences that are learned from the community-contributed data. To this end, this paper models the social, categorical, geographical, sequential, and temporal influences on the visiting preferences of users to POIs.

References

[1]
H. Gao, J. Tang, X. Hu, and H. Liu. Content-aware point of interest recommendation on location-based social networks. In AAAI, pages 1721--1727, 2015.
[2]
Yelp. Challenge Data Set. http://www.yelp.com/dataset_challenge, 2014.
[3]
J.-D. Zhang and C.-Y. Chow. iGSLR: Personalized geo-social location recommendation - a kernel density estimation approach. In ACM SIGSPATIAL, pages 334--343, 2013.
[4]
J.-D. Zhang and C.-Y. Chow. CoRe: Exploiting the personalized influence of two-dimensional geographic coordinates for location recommendations. Information Sciences, 293:163--181, 2015.
[5]
J.-D. Zhang and C.-Y. Chow. GeoSoCa: Exploiting geographical, social and categorical correlations for point-of-interest recommendations. In ACM SIGIR, pages 443--452, 2015.
[6]
J.-D. Zhang and C.-Y. Chow. Spatiotemporal sequential influence modeling for location recommendations: A gravity-based approach. ACM TIST, 7(1):11:1--11:25, 2015.
[7]
J.-D. Zhang and C.-Y. Chow. TICRec: A probabilistic framework to utilize temporal influence correlations for time-aware location recommendations. IEEE TSC, accepted, 2015.
[8]
J.-D. Zhang, C.-Y. Chow, and Y. Li. LORE: Exploiting sequential influence for location recommendations. In ACM SIGSPATIAL, pages 103--112, 2014.
[9]
J.-D. Zhang, C.-Y. Chow, and Y. Li. iGeoRec: A personalized and efficient geographical location recommendation framework. IEEE TSC, 8(5):701--714, 2015.
[10]
J.-D. Zhang, C.-Y. Chow, and Y. Zheng. ORec: An opinion-based point-of-interest recommendation framework. In ACM CIKM, pages 1641--1650, 2015.

Cited By

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  • (2024)Towards Privacy-Preserving Category-Aware POI Recommendation over Encrypted LBSN DataInformation Sciences10.1016/j.ins.2024.120253(120253)Online publication date: Feb-2024
  • (2023)Revisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest RecommendationProceedings of the 31st ACM International Conference on Advances in Geographic Information Systems10.1145/3589132.3625644(1-10)Online publication date: 13-Nov-2023
  • (2023)TeSP-TMF: A temporal-aware personalized POI recommendation approach based on potential preferences and grey relational analysisElectronic Commerce Research and Applications10.1016/j.elerap.2023.10124358(101243)Online publication date: Mar-2023
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Published In

cover image SIGSPATIAL Special
SIGSPATIAL Special  Volume 7, Issue 3
November 2015
38 pages
EISSN:1946-7729
DOI:10.1145/2876480
Issue’s Table of Contents

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 January 2016
Published in SIGSPATIAL Volume 7, Issue 3

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Cited By

View all
  • (2024)Towards Privacy-Preserving Category-Aware POI Recommendation over Encrypted LBSN DataInformation Sciences10.1016/j.ins.2024.120253(120253)Online publication date: Feb-2024
  • (2023)Revisiting Mobility Modeling with Graph: A Graph Transformer Model for Next Point-of-Interest RecommendationProceedings of the 31st ACM International Conference on Advances in Geographic Information Systems10.1145/3589132.3625644(1-10)Online publication date: 13-Nov-2023
  • (2023)TeSP-TMF: A temporal-aware personalized POI recommendation approach based on potential preferences and grey relational analysisElectronic Commerce Research and Applications10.1016/j.elerap.2023.10124358(101243)Online publication date: Mar-2023
  • (2023)Incremental tree-based successive POI recommendation in location-based social networksApplied Intelligence10.1007/s10489-022-03842-453:7(7562-7598)Online publication date: 1-Apr-2023
  • (2021)Joint Selection of Influential Users and Locations under Target Region in Location-Based Social NetworksSensors10.3390/s2103070921:3(709)Online publication date: 21-Jan-2021
  • (2021)Successive Point-of-Interest Recommendation With Personalized Local Differential PrivacyIEEE Transactions on Vehicular Technology10.1109/TVT.2021.310846370:10(10477-10488)Online publication date: Oct-2021
  • (2021)Leveraging contextual influence and user preferences for point-of-interest recommendationMultimedia Tools and Applications10.1007/s11042-020-09746-080:1(1487-1501)Online publication date: 1-Jan-2021
  • (2020)Location-based social simulation for prescriptive analytics of disease spreadSIGSPATIAL Special10.1145/3404820.340482812:1(53-61)Online publication date: 8-Jul-2020
  • (2020)Multi-factor Fusion POI Recommendation ModelData Science10.1007/978-981-15-7984-4_2(21-35)Online publication date: 20-Aug-2020
  • (2020)Location‐based social network recommendations with computational intelligence‐based similarity computation and user check‐in behaviorConcurrency and Computation: Practice and Experience10.1002/cpe.610633:22Online publication date: 24-Nov-2020
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