| 面向Web日志的语义聚类算法* |
| |
| 引用本文： | 潘钧.面向Web日志的语义聚类算法*[J].计算机应用研究,2007,24(7):267-269. |
| |
| 作者姓名： | 潘钧 |
| |
| 作者单位： | 扬州大学,信息工程学院,江苏,扬州,225009 |
| |
| 基金项目： | 国家自然科学基金
,
江苏省自然科学基金 |
| |
| 摘 要： | 由于现有的Web日志缺少明显语义,提出一种语义Web日志模型--SWLM,并给出基于该模型的网页和用户聚类算法.通过日志概念的语义距离定量计算来聚类网页和用户,奠定了Web个性化服务的基础.性能测试实验证明,该模型具有较好的整体性能,能有效地进行网页和用户聚类.
|
| 关 键 词： | Web日志 挖掘 语义 本体 日志 语义距离 聚类算法 Web Log Oriented Clustering Algorithm 用户聚类 整体性能 验证 性能测试 性化服务 定量计算 网页 模型 |
| 文章编号： | 1001-3695（2007）07-0267-03 |
| 修稿时间： | 2006-06-012006-08-03 |
Semantic Clustering Algorithm Oriented to Web Log |
| |
| PAN Jun.Semantic Clustering Algorithm Oriented to Web Log[J].Application Research of Computers,2007,24(7):267-269. |
| |
| Authors: | PAN Jun |
| |
| Affiliation: | School of Information Engineering, Yangzhou University, Yangzhou Jiangsu 225009, China |
| |
| Abstract: | Existed Web logs were lack of semantics obviously. To improved the efficiency and accuracy of Web mining, a semantic Web log model SWLM was presented, and two algorithms based on this model was given to cluster pages and users. Then, the semantic information could be mining from the Web log, and the semantic distances of log concepts could be computed. The test experiment shows that this model has better performance and clusters pages and users effectively. Those results can facilitate personalized services and user modeling. |
| |
| Keywords: | Web log mining semantic ontology |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《计算机应用研究》浏览原始摘要信息 |
|
点击此处可从《计算机应用研究》下载全文 |
|
