基于畅销书及意见领袖的图书推荐系统
BOOK RECOMMENDATION SYSTEM BASED ON OPINION LEADERS AND POPULAR BOOKS
成胤钟1
作者信息
- 1. 重庆文化艺术职业学院 重庆 400067
- 折叠
摘要
在读者向图书馆借阅图书或从书店购买图书的过程中,名人推荐及畅销书榜单对读者的选择具有很大的影响.针对这种情况,结合影响力分析和主题模型提出新的图书协同过滤推荐系统.算法结合最大熵和最大方差来选择评分矩阵的影响力用户和影响力项目,基于建立的密集矩阵预测未知评分.运用改进的聚类算法对词向量进行聚类处理,建立主题.在公开的数据集上完成验证实验,结果表明该算法提高了图书推荐系统的性能.
Abstract
When readers borrow books from libraries or purchase books from shops,both celebrity recommended books and best seller list have a big influence to the selection of readers.In view of this,we propose a new book collaborative filtering recommendation system,which combines influence analysis and topic model.This algorithm combined maximum entropy and maximum variance to select the influential users and influential items in the rating matrix,and it predicted the unknown ratings based on the dense matrix.The algorithm applied enhanced clustering algorithm to cluster the word vectors,as a result,the topics of texts were constructed.Validation experiments were carried on public datasets.The results show that the proposed algorithm improves the performance of book recommendation system.
关键词
图书推荐系统/主题模型/球面k均值聚类/最大熵/协同过滤/意见领袖Key words
Book recommendation system/Topic model/Spherical k-means clustering/Maximum entropy/Collab-orative filtering/Opinion leader引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
维普
万方数据