Point-of-Interest Recommendation with Spatio-Temporal Context Awareness

doi:10.13190/j.jbupt.2017-081

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2018, Vol. 41 ›› Issue (1): 37-42,50.doi: 10.13190/j.jbupt.2017-081

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Point-of-Interest Recommendation with Spatio-Temporal Context Awareness

XU Qian-fang¹, WANG Jia-chun¹, XIAO Bo^1,2

1. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. Institute of Sensing Technology and Business, Beijing University of Posts and Telecommunications, Jiangsu Wuxi 214135, China

Received:2017-05-12 Online:2018-02-28 Published:2018-01-04

Abstract

Abstract: A personalized hybrid point-of-interest recommendation with spatio-temporal context awareness was proposed to provide users in location-based social networks with superior service. Spatially, two-dimension kernel density estimation was performed for each cluster of check-ins derived by hierarchical clustering and averaged. Meanwhile, random walk on graph was iterated on transition matrices generated from sequence information, location information and social network. The hybrid model combines spatio-temporal context above for recommendation. Experiment on real-world location-based social network(LBSN) datasets demonstrates that the performance metrics of precision and recall of the hybrid recommendation model is superior to other baseline techniques in both standard recommendation scene and cold-start scene.

Key words: location-based social networks, spatio-temporal context awareness, point-of-interest recommendation, random walk on graph

CLC Number:

TP301

XU Qian-fang, WANG Jia-chun, XIAO Bo. Point-of-Interest Recommendation with Spatio-Temporal Context Awareness[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2018, 41(1): 37-42,50.

References

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Point-of-Interest Recommendation with Spatio-Temporal Context Awareness

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