基于CLV偏好挖掘模型的数字社区用户偏好挖掘研究

Pupose/Significance] Digital communities have become a way for enterprises to manage users efficiently. The exitingresearch on digital community rarely considers the importance of user behavior information and user's customer life cycle value to themining of user preferences in digital community. This research aims to give full play to the digital communityts characteristics such asintuitive, convenient, interestng. and interactive properties so that the research resuts can benefit every user in their use of the digita1community and every enterprise in their user management.[MethodProcess] Aiming at the user groups in digital conmunity, this paperproposes a preference nining model ClV-Prefcrence mining (CLV-PM) based on Customer Lifetime Vatue (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 groupcharacteristics of users are mined through K-mean t+t algonithm to generate user vahue category labels. Second, in order to consider thetimeliness and difference of users and enhance the model's cognition of preferences, this paper uses the entropy weight method to sotvethe indicator weights of each activity, obtains user CLV to constuct user-project scoring matrix, and uses the collaborative filteringalzorithm to predict user preferences.Finally, based on the user value category, user historical preference and user forecast preference,the user preference profile of target users in dgital community is generated, and feasible suggestions are put forward for the cperationand maintenance of target users according to the user prefcrence profile.[ResutsiConchusions] The user dataset of the "Wechatcommunity" management platfom can be divided into four user vahue categories: important vatue users, ow valbue users, rehuned usersand important retention users. Target users 16254 are important value users, and the operation strategy of "retention and maintenance" isadopted. The historical preferences are happy hop, sec-kill and other activities; the prediction preference is flying chess battle, guessingcode map and other activities; the target user preference sketch provides the basis for the operation and maintenance of users in thedgital community. In terms of data source, the CLV-PM model proposed in this paper drectly reflects user preferences based on userbehavior information and reduces the problem of score distotion.To provide a new perspective for the research of user behavior indigital community, the construction of user-project scoring matix based on userCLV fully considers the user value of digital communityand provides a new direction for the extension and application of CLV.However, due to limited research space, this paper did notconduct model evaluation research on the proposed model which can be further discussed in subsequent studies.