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

[1] BENEVENUTO F,RODRIGUES T,CHA M,et al.Characterizing user behavior in online social networks[C]∥Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference.ACM,2009:49-62.
[2] SCELLATO S,NOULAS A,MASCOLO C.Exploiting placefeatures in link prediction on location-based social networks[C]∥ACM SIGKDD International Conference on Knowledge Disco-very and Data Mining.ACM,2011:1046-1054.
[3] BAO J,ZHENG Y,WILKIE D,et al.Recommendations in location-based social networks:a survey[J].GeoInformatica,2015,9(3):525-565.
[4] FERENCE G,YE M,LEE W C.Location recommendation forout-of-town users in location-based social networks[C]∥ACM International Conference on Conference on Information & Knowledge Management.2013:721-726.
[5] ZHANG J D,CHOW C Y.CoRe:Exploiting the personalized influence of two-dimensional geographic coordinates for location recommendations[J].Information Sciences,2015,3:163-181.
[6] YE M,YIN P,LEE W C.Location recommendation for location-based social networks[C]∥Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems.ACM,2010:458-461.
[7] JAMALI M,ESTER M.A matrix factorization technique with trust propagation for recommendation in social networks[C]∥ACM Conference on Recommender Systems,Recsys 2010.Barcelona,Spain,2010:1055-1066.
[8] CAVERLEE J,LIU L,WEBB S.The social trust framework for trusted social information management:architecture and algorithms[J].Information Sciences An International Journal,2010,0(1):95-112.
[9] GHIOCA D.Hierarchical geographical modeling of user loca-tions from social media posts[C]∥International Conference on World Wide Web.2013:25-36.
[10] GAO M,JIN C Q,QIAN W N,et al.Real-time and personalized recommendation on microblogging systems[J].Chinese Journal of Computers,2014,37(4):963-975.(in Chinese) 高明,金澈清,钱卫宁,等.面向微博系统的实时个性化推荐[J].计算机学报,2014,7(4):963-975.
[11] CHENG C,YANG H,KING I,et al.Fused matrix factorization with geographical and social influence in location-based social networks[C]∥Proc of the 26th AAAI Conf on Artificial Intelligence(AAAI’12).Menlo Park,CA:AAAI,2012:211-276.
[12] ZHAO G,QIAN X,KANG C.Service Rating Prediction by Exploring Social Mobile Users’ Geographic Locations[J].IEEE Transactions on Big Data,2017(99):67-78.
[13] FERENCE G,YE M,LEE W C.Location recommendation for out-of-town users in location-based social networks[C]//Proceedings of the 22nd ACM International Conference on Information & Knowledge Management.ACM,2013:721-726.
[14] DEL PRETE L,CAPRA L.diffeRS:A Mobile RecommenderService[C]∥Eleventh International Conference on Mobile Data Management,MDM 2010.Kanas City,Missouri,USA,2010:21-26.
[15] MNIH A,SALAKHUTDINOV R.Probabilistic matrix factorization[C]∥International Conference on Machine Learning.2012:880-887.
[16] LEE D D,SEUNG H S.Learning the parts of objects by non-negativ matrix factorization[J].Nature,1999,1(6755):788-791.
[17] YE M,YIN P,LEE W C,et al.Exploiting geographical influence for collaborative point-of-interest recommendation[C]∥ International ACM SIGIR Conference on Research and Development in Information Retrieval.ACM,2011:325-334.

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