| 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 |
| 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 |
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| DOI： |
| 中文关键词: SOM神经网络;聚类分析;个性化推荐;关联数据集 |
| 英文关键词: SOM Neural Network;Cluster Analysis;Personalized Recommendation;Linked Data Sets |
| 基金项目: |
| 作者 | 单位 | | 刘爱琴 | 山西大学 | | 李永清 | 中国石油大学(华东)东营校区 |
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| 摘要点击次数: 1880 |
| 全文下载次数: 1387 |
| 中文摘要: |
| 借助SOM神经网络聚类算法无参数、精准度高的特点,本文对山西大学图书馆的Web访问行为进行聚类和优化分析.将聚类行为分为指数函数粗调整和线性函数微调整两个优化阶段,有效提升聚类速率和聚类效果.基于对用户分析结果的输出,将用户个人特征信息、用户行为数据以及文献数据库进行筛选整合,形成可靠性和可用性更高的关联数据集,并结合语义检索和属性值匹配等技术建构用户个性化服务推荐系统,进行有效性验证,实现图书馆内部主题推荐、图书推荐和专家推荐三个子系统的协同. |
| 英文摘要: |
| 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. |
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