JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (3): 44-50.doi: 10.6040/j.issn.1672-3961.0.2015.295

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The method of spot cluster recommendation in location-based social networks

LI Shuo, SHI Yuliang   

  1. School of Software Engineering, Beijing University of Technology, Beijing 100124, China
  • Received:2015-09-06 Online:2016-06-30 Published:2015-09-06

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Abstract: In order to solve the data sparse and cold start in spot recommendation in the location-based social networking, an improved spot recommendation method was proposed. Based on the clustering algorithm and the collaborative filtering algorithm, the user preferences, friend relations, semantic location and other factors was taken into account. The advantages of the two methods were complemented. The focus of this research was the calculation of similarity, which included location similarity, friends intimacy measure, term frequency inverse document frequency, cosine similarity.To verify the proposed methods, precision, recall,mean average precision was used as a measure on Foursquare dataset. The results showed that the proposed method could effectively improve the recommendation effect.

Key words: clustering, collaborative filtering, location-based social network, spot recommendation

CLC Number: 

  • TP391
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