Application And Research On Data Mining In CRM Of Local Tax Industry

Recently, data Mining in Customer Relationship Management System is paidmore and more attention by researchers in many fields, such as banking, postal services,mobile, manufacturing, wholesale, retail, telecommunications, real estate, medical,IT, media, transportation and logistics industry. This paper focuses on the research andapplication on data mining clustering in the local tax customer relationship managementsystem.At present, only a few customer relationship management systems are used inlocal tax industry, and even fewer customer relationship management systems whichuse data mining. Firstly, this paper expounds the framework of customer relationshipmanagement system and its application status in local tax industry, Secondly, we havestudied some data mining clustering algorithms such as k-means algorithm, DBSCANalgorithm and AP clustering algorithm. Finally, aiming at land tax industry customerdata information, we propose a hybrid clustering algorithm based on Kmedia andDBSCAN, and deal with the customer information data and use clustering algorithm onthe clustering analysis, for providing policymakers strong basis. Experimental resultsverify the data mining application in land tax industry are feasible and effective.