Measuring Users Relationship Strength Using A Model Based On Hierarchical Voting

Smart phones have become an integral part of daily life communication tools,we can collect intelligently location,call logs,text messages,WeChat anywhere which reflect a variety of information daily interactions and social relations between people.People interaction frequency,time,location,distance and the similarity of trajectory information reflects the strength of the relationship and the relationship between people.Relationship strength reflects the degree of intimacy between two different persons,which is of great importance in analyzing human's social relationship as well as social network.In this paper,we propose a URSHV(User Relationship Strength Hierarchy Vote),which can measure the relationship between people in daily life through GPS data from three levels,namely: daily trajectory,semantic locations and semantic labels.To sum up,the main research contents and contributions are as follows:First of all,the strength of the relationship between users and semantic location with semantic labels are closely related,this paper uses segmented kalman filtering algorithm on GPS trajectory data to de-noising;using the clustering algorithm based on density of position trajectory data clustering,and form a semantic position;on this basis,the semantic annotation mechanism based on Rules,the semantic annotation of semantic encoding,geographic location by anti semantic label inference and input auto completion etc;the GPS position trajectory data sequence clustering into meaningful semantic position and semantic labels,which laid the foundation for the semantic location and semantic labels based on the strength calculation of the relationship between users.Secondly,in order to calculate the strength of the relationship between users from the three levels of trajectory data,semantic location and semantic labels,using DTW model of spatial distance calculation between users to measure the similarity between the users,the use of trajectory sequence similarity of users every day to track the entropy weighting processing,and the strength of relationship between users the LDA were calculated using the topic model;semantic locations similarity and semantic labels based on behavior patterns among users,as the strength of the relationship between users;measurement results of three levels of the ensemble learning theory to vote,to vote as the strength of relationship between end users.Finally,on the basis of the above study,based on the MIT reality mining project of publicly available data sets,similarity between users by using the data set of the questionnaire,users construct between a real relationship strength as a benchmark for testing proposed an inverse logarithmic induced score measurement method to measure the strength of the relationship between users based on,and effectiveness model of URSHV for experiments,the results show that the model can effectively measure the strength of the relationship between users.