User Precision Profile Based On Multi-source Perception Data And Its Application Research

With the increasing intelligentization and integration of mobile terminal devices(including smart phones,wearable devices,etc.),the comprehensive perception and thorough understanding of user behaviors can be realized by making full use of all kinds of embedded sensors,such as microphone,gyroscope,WiFi,Bluetooth,etc.On this basis,the construction of accurate user portraits has a very important role and significance for key population monitoring,accurate business recommendation,personalized service and other applications.In reality,however,the user behavior characteristics/law is often scattered in the real physical world,virtual information space,and secret inner world,therefore,in order to realize accurate portrait of users must be found scattered in different space and dimension of multi-source data fusion effectively perception,the construction of a unified,integration of user picture frame.Based on this,this paper carries out a research on accurate user portrait based on multi-source perception data.Specific research contents include the following aspects:(1)Personality psychological space:The big five personality model and psychological model are depicted through multi-source data of mobile phone perception.Choice method of variance,and Pearson correlation coefficient method is used to extract the characteristics of the significant correlation with personality psychological questionnaire results,using recursive feature elimination method for feature selection,use after training logistic regression model,support vector machine(SVM)model and random forest model respectively to forecast the big five personality and psychological state,get nine dimensional vector said big five personality model(5 dims)and the predictions of a mental model(4 dims).(2)Information space:Use the communication data generated by mobile phones to depict users' social relations.The communication data contains the unique identification marks of mobile phone users.Based on the frequency and duration of communication between users,social networks are constructed on weekends in a week.The performance of social trust and influence of users in communication networks is studied,which becomes an important indicator to measure the closeness of user relationships.(3)Physical space:The location perception data generated in the mobile scene describes the user's movement distribution relationship,location semantics and movement behavior characteristics.The distribution of bluetooth connection of different users can be analyzed to find the mobile distribution relation of users.Tf-idf classification method is used to extract location semantics and mark the user's access location preference.Establish a social relation network on the weekend of a week for the frequency and duration of acquired Bluetooth connection to distinguish the mobile behavior characteristics of users on the weekend of a week.On this basis,in order to effectively verify the multi-source data-based user accurate portrait method constructed in this paper,it is applied to mobile swarm intelligence application service.Specifically,the user's mobile behavior and social relations portrait respectively applied to distribute task offline and online distribution,offline tasks distribution stage task allocation method based on utility function are presented,with the task,task completion compared with the traditional tasks distribution method and task distribution success rate increased by 10%on average;In the online task distribution stage,a task forwarding method based on social relationship portrait was proposed.In the task transfer experiment involving social relationship,user's credit value and physical distance,the task completion rate in the task transfer experiment involving only user's credit value and physical distance was increased by 15%on average.