数字图书馆论坛Issue(10)：26-31,6.DOI:10.3772/j.issn.1673-2286.2017.10.005
基于改进K均值算法的移动图书馆用户评论需求聚类研究
Research on Demand Clustering of Mobile Library from User Reviews Based on the Improved K-means Algorithm
摘要
Abstract
The automatic clustering of mobile library user reviews helps to obtain user needs more accurately and efficiently. Based on the traditional K-means algorithm, this paper uses HT-LaD algorithm to improve the initial clustering center and uses the user's evaluation data of mobile library to prove it. The results show that it is feasible to use the improved K-means algorithm to complete the demand clustering of mobile library user comment text, and the clustering accuracy and stability are improved.关键词
移动图书馆/改进K均值聚类/用户评论/用户需求Key words
Mobile Library/Improved K-means Algorithm/User Reviews/User Demands分类
社会科学引用本文复制引用
郑德俊,朱婷婷,沈军威..基于改进K均值算法的移动图书馆用户评论需求聚类研究[J].数字图书馆论坛,2017,(10):26-31,6.基金项目
本研究得到国家社会科学基金项目"基于用户感知的移动图书馆服务质量评价及提升策略研究"(编号:13BTQ026)资助. （编号:13BTQ026）
