【作者】 徐仰彬；

【导师】 刘志镜；

【作者基本信息】 西安电子科技大学 ， 计算机应用技术， 2007， 硕士

【摘要】 随着信息技术的发展,以电子形式存在的文本信息已经成为人们主要的信息来源。人们迫切需要能够从Web上快速、有效地发现资源和知识的工具。近年来针对文本数据的文本挖掘已逐渐成为人们研究的新课题。其中,对于文本聚类的研究己经引起了广泛的重视,并取得了良好的成果。本文首先对数据挖掘流程以及数据挖掘分类和各自的研究现状及发展进行了概括的介绍;然后结合汉语自身的相关特点详细的分析了中文文本自动聚类中所涉及到的关键问题及其技术;接着介绍了人工神经网络技术的发展的现状和特点及其在聚类中的应用。人工神经网络由大量简单的基本元件-神经元相互联结,模拟人的大脑神经处理信息的方式,进行信息并行处理和非线性转换的复杂网络系统。本文将人工神经网络技术和文本挖掘技术结合,并应用于搜索引擎中的结果分析中。在此基础上提出了基于SOM神经网络的文本挖掘模型。更多还原

【Abstract】 With the development of information technology, electronic texts have become more and more Popular as source of information .People need some tool to find resource and knowledge from the Web urgently. Text mining had become a new promising research subject, especially in Text Clustering, in recent years.In this paper, we firstly make a general introduction about the DM processes, DM classification and research, developing based on that. After that, with some characteristic of Chinese, we discuss several pivotal topics on Chinese text classifying in data .Then, we introduced artificial neural network and apply it to Text Clustering.Artificial neural network comprises a great deal of basic elements,neural unit connected one another. It can simulate human being’s brain neural to deal with information and implement parallel treating and non-linear conversion. In this paper, we companies artificial neural network and text mining, then applied in the fields of Text mining. On the base of studying, put forward SOM neural network based companies Text mining system.更多还原