因特网文本智能挖掘的模糊聚类算法研究  

A Fuzzy Clustering Algorithm for Intelligent Mining of Internet Texts

作　　者：王晓勇[1] 肖四友[1] 张文祥[1] 

机构地区：[1]浙江万里学院智能控制研究所,浙江宁波315100

出　　处：《计算机仿真》2009年第7期216-219,共4页Computer Simulation

摘　　要：随着Internet的深入发展及普及应用,网络中可获取的大部分文本信息由来自各种数据源的文档组成。由于电子形式的文本信息飞速增涨,可以获知的文本信息已成海量之势,文本挖掘已经成为信息领域的研究热点,快速得到目标文本成为互联网发展的瓶颈。在动态聚类方法和基于特征属性分类法的基础上提出基于混合模糊聚类理论的文本数据分类系统新模型,在模型基础上探究了一种模糊聚类仿真算法,通过实验验证算法能有效提高文本分类效率及文本分类准确率,从而在实际网络文本挖掘应用中快速得到目标文本,实现因特网文本智能挖掘。With the further development and widespread application of Internet, most securable text information on Internet is made up of numerous files from various kinds of data source. By the swift growth of electronic version text information, the securable text information is numberless as the sand, and Text Mining becomes the focal point of re- search. How to find the target text quickly is now the bottleneck to the development of Internet. The paper mainly analyses a new text - classification model based on Hybrid Fuzzy Clustering Theory, which is brought forth on ground of dynamic cluster model and the means of classification according to the attribute property. And based on that new model, the paper explores the simulation algorithm of fuzzy clustering, which is testified to be able to highly improve the efficiency and precision of text - classification, so as to find the object files quickly in practical application of web - text mining and realize intelligent excavation of text on Internet.

关 键 词：因特网文本 混合模糊聚类 文本智能挖掘 仿真算法 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]