数字图书馆论坛Issue(10)：32-38,7.DOI:10.3772/j.issn.1673-2286.2017.10.006
基于SOM神经网络的高校图书馆个性化需求挖掘系统研究
Research on Personalized Demand Mining System of University Library Based on SOM
刘爱琴 1李永清2
作者信息
- 1. 山西大学经济与管理学院,太原030006
- 2. 中国石油大学[华东]经济与管理学院,青岛266555
- 折叠
摘要
Abstract
According to the characteristics of high precision and no parameter of the SOM neural network clustering algorithm, the paper, taking the web access behaviors of users in Shanxi University Library as an example, carried on optimized cluster analysis. The progress of clustering behavior could be divided into two stages, the rough adjustment training and the micro-adjustment training, which could improve the clustering rate and effect. Based on the output of analysis results, screening and integrating the user's personal characteristic information, users' behavior data and literature database, to linked data set reliable and available highly. And combining with the semantic retrieval and at ributing matching technology, the user personalized service recommendation system was formed and verified effective. It realized the coordination among internal subjects recommending, books recommending and experts recommending.关键词
SOM神经网络/聚类分析/个性化推荐/关联数据集Key words
SOM Neural Network/Cluster Analysis/Personalized Recommendation/Linked Data Sets分类
社会科学引用本文复制引用
刘爱琴,李永清..基于SOM神经网络的高校图书馆个性化需求挖掘系统研究[J].数字图书馆论坛,2017,(10):32-38,7.
