| Web文本聚类算法WTCA的研究与实现 |
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| 引用本文： | 郑煜,钱榕.Web文本聚类算法WTCA的研究与实现[J].计算机工程与应用,2007,43(4):170-172. |
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| 作者姓名： | 郑煜 钱榕 |
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| 作者单位： | 1. 东北林业大学,理学院,数学系,哈尔滨,150040
2. 北京科技大学,信息工程学院,北京,100083 |
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| 摘 要： | 提出了一种新的Web文本聚类算法WTCA——基于自组织特征映射神经网络(SOM)的聚类算法。该算法分为训练SOM网络及聚类分析两个阶段,具有自稳定性,无须外界给出评价函数;能够识别概念空间中最有意义的特征,抗噪音能力强。该算法应用到现代远程教育网,可以对各类远程教育站点上收集的文本资料信息自动进行聚类分析;从海量Web文本信息源中快速有效地获取重要的知识。
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| 关 键 词： | Web文本挖掘 文本聚类 非结构化数据挖掘结构模型 自组织特征映射 |
| 文章编号： | 1002-8331（2007）04-0170-03 |
| 修稿时间： | 2006-09 |
Research and implementation of Web text clustering algorithm WTCA |
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| ZHENG Yu,QIAN Rong.Research and implementation of Web text clustering algorithm WTCA[J].Computer Engineering and Applications,2007,43(4):170-172. |
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| Authors: | ZHENG Yu QIAN Rong |
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| Affiliation: | 1.College of Science, Northeast Forestry University, Harbin 150040, China 2.School of Information Engineering, University of Science and Technology Beijing, Beijing 100083, China |
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| Abstract: | In this paper,we present a new algorithm of Web text clustering mining WTCA.This algorithm includes the training stage and the clustering stage of SOM network.It can distinguish the most meaningful features from the Concept Space without the evaluation function.The algorithm has been applied to the Modern Long-distance Education Net.It can automatically congregate the text information of education field,which is collected from education sites and help people to browse the important information quickly by information navigation mechanism and acquire useful knowledge. |
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| Keywords: | Web text mining text clustering nonstructural data mining Self-Organization Feature Mapping(SOM) |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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