Computer Science ›› 2017, Vol. 44 ›› Issue (12): 245-248, 278.doi: 10.11896/j.issn.1002-137X.2017.12.044

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Point-of-interest Recommendation Based on Comment Text in Location Social Network

WANG Xiao-yan, YUAN Jing-ling and QIN Feng   

  • Online:2018-12-01 Published:2018-12-01

Abstract: With the rapid development of the location-based social networks(LBSN), the point-of-interest(POI) recommendation is becoming more and more important to users and businesses.At present,the recommendation algorithm based on social network mainly uses the user’s historical data and social network data to improve the quality of recommendation,but ignores the POI’s comment text data.And the data in LBSN often have some missing information, how to guarantee robustness is a huge challenge for the point-of-interest recommendation algorithms.To this end,this paper proposed a new model of point-of-interest recommendation,called SoGeoCom model.The model combines the user’s social network data,geographic location data and the POI’s comment text data to carry on the POI recommendation.Experimental results based on real data set from Yelp show that,compared with other mainstream POI recommendation models,the SoGeoCom model can improve the precision and recall rate,have good robustness,and get a better recommendation effect.

Key words: User point-of-interest recommendation,Social networks,Comment text,Geographical information

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