Individual Location Recommendation for Location-Based Social Network

doi:10.13190/j.jbupt.2015.05.023

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2015, Vol. 38 ›› Issue (5): 118-124.doi: 10.13190/j.jbupt.2015.05.023

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Individual Location Recommendation for Location-Based Social Network

XU Ya-bin^1,2, SUN Xiao-chen¹

1. School of Computer, Beijing Information Science and Technology University, Beijing 100101, China;
2. Beijing Key Laboratory of Internet Culture and Digital Dissemination Research, Beijing 100101, China

Received:2015-01-08 Online:2015-10-28 Published:2015-10-28

Abstract

Abstract:

In order to effectively improve the users' experience for location social networks, a model of personalized location recommendation service was proposed. Considering the users' check-in behavior features, the users' characteristics and semantic features of interested location point, this model combines the ant colony algorithm with the improved hybrid collaborative filtering algorithm to improve the quality and efficiency of the individual location recommendation. Experiments show that, the recall, accuracy and average absolute error value of the location recommendation model proposed in this article is superior to the existing methods.

Key words: location-based social network, individual location recommendation, location-based service, collaborative filtering

CLC Number:

TP301

XU Ya-bin, SUN Xiao-chen. Individual Location Recommendation for Location-Based Social Network[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2015, 38(5): 118-124.

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Individual Location Recommendation for Location-Based Social Network

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