A Recommender System Research Based on LocationBa

Authors: Jianmin Wang Ruhuo Tan RiPeng Zhang Fang You

Publish Date: 2016/7/17

Volume: , Issue: , Pages: 81-90

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Abstract

Nowadays with the rapid development of LocationBased Social Networks information presents a trend of explosive growth In order to locate the valuable information in tremendous amounts of locationbased service data and prosperi O2O business through LBS recommender system based on locationbased service was presented This paper takes Sina Microblog LBS data as research object By analyzing the features of the crawled data and the existing problems of current LBS recommender systems we present Regiondensitybased Clustering RC recommendation algorithm For optimization this paper also presents another algorithm called DistanceandCategorybased Clustering DCC This algorithm is mainly about clustering spots base on their distance similarity and category similarity If two spots are nearby and both category attributes are similar they will be more likely to gathered into a cluster Finally this paper also proposed the visualization method of the LBSNs recommender systemThis work was supported by the National Natural Science Foundation of China under Grant Nos 61073132 and 60776796 the Fundamental Research Funds for the Central Universities 101gpy33 Special Project on the Integration of Industry Education and Research of Guangdong Province No 2012B091000062 Project 985 of Innovation Base for Journalism Communication in the Allmedia Era Sun Yatsen University

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