User Preference Mining in Digital Community Based on CLV Preference Mining Model

[Purpose/Significance] Digital communities have become a way for enterprises to manage users efficiently. The existing research on digital community rarely considers the importance of user behavior information and user's customer life cycle value to the mining of user preferences in digital community. This research aims to give full play to the digital community's characteristics such as intuitive, convenient, interesting, and interactive properties so that the research results can benefit every user in their use of the digital community and every enterprise in their user management. [Method/Process] Aiming at the user groups in digital community, this paper proposes a preference mining model ClV-Preference mining (CLV-PM) based on Customer Lifetime Value (CLV). First, in order to reflect the real preferences of users, the three indicators of the RFM model are used to quantify user behavior information, and the group characteristics of users are mined through K-mean ++ algorithm to generate user value categor