文本挖掘技术研究进展*

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。

Survey of Text Mining Technology

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 feature selection, automatic abstracting, text categorization, text clustering, text association, data visualization. In the end, it shows the importance of text mining in knowledge discovery and highlights the upcoming challenges of text mining and the opportunities it offers.