文献类型：期刊文献

英文题名：An Improved Algorithm of Mixed Cooperative Filter Recommendation Based on Project and User

作者：Luo, Yongjun[1]; Zheng, Hong[1]

机构：[1] School of Information Science and Engineering, East China University of Science and Technology, Shanghai, 200237, China

年份：2020

卷号：675

起止页码：813

外文期刊名：Lecture Notes in Electrical Engineering

收录：EI(收录号：20204109326481)

语种：英文

外文关键词：Clustering algorithms - Nearest neighbor search

摘要：The traditional collaborative filtering algorithm ignores the impact of the time factor when searching the nearest neighbor set, only from the user or item takes into account the similarity of the user or item unilaterally, and ignores the impact of user characteristics on the recommendation. Aiming to the above problems, the paper introduced the time forgotten function, resources viscosity function and the user feature vector, also improved the process of finding the user’s nearest neighbor set, which reflected the time effect, degree of user preferences and user characteristic. The traditional algorithm consumes too many resources to search the nearest neighbor set, as well as the reliability is poor. In the paper, a novel recommendation algorithm based on user clustering of item attributes is proposed. ? 2020, Springer Nature Singapore Pte Ltd.