摘要
文本挖掘是一个对具有丰富语义的文本进行分析从而理解其所包含的内容和意义的过程,已经成为数据挖掘中一个日益流行而重要的研究领域。首先给出了文本挖掘的定义和框架,对文本挖掘中预处理、文本摘要、文本分类、聚类、关联分析及可视化技术进行了详尽的分析,并归纳了最新的研究进展。最后指出了文本挖掘在知识发现中的重要意义,展望了文本挖掘在信息技术中的发展前景。
Text Mining, also known as intelligent text analysis, text data mining or Knowledge-Discovery in Text (KDT), is a rapidly emerging field concerned with the extraction of concepts, relations, and implicit knowledge from texts. As most information ( over 80% ) is stored as text, text mining is believed to have a high commercial potential value. Firstly, this review paper discusses the research status of text mining, then it lays out the framework of text mining and analyses techniques of text mining, such as teature selection, automatic abstracting, text categorization, text clustering, text association, data visualization. In the end, it shows the importance of text mining in knowledge disc.overy and highlights the upcoming challenges of text mining and the opportunities it offers.
出处
《计算机应用研究》
CSCD
北大核心
2006年第2期1-4,共4页
Application Research of Computers
基金
国家自然科学基金资助项目(70031010)
北京理工大学学校基金项目
北京理工大学育苗基金项目
关键词
文本挖掘
中文分词
特征选取
文本摘要
文本分类
文本聚类
关联分析
数据可视化
Text Mining
Cutting Chinese Word
Feature Selection
Text Automatic Abstracting
Text Categorization
Text Clustering
Text Association
Data Visualization