基于文本的数据挖掘

Chris Clifton, Rick Steinheiser
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引用次数: 20

摘要

数据挖掘技术使我们能够从大量结构化数据中提取有意义的模式。信息检索系统提供了大量的文本数据。从这些数据中提取有意义的模式是困难的。目前用于挖掘结构化数据的工具不适合自由文本。我们概述了文本中的知识发现中涉及的问题,并提出了一个用于提取跨多个文档的模式的体系结构。说明了这样一个系统可以提供的功能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data mining on text
Data mining technology is giving us the ability to extract meaningful patterns from large quantities of structured data. Information retrieval systems have made large quantities of textual data available. Extracting meaningful patterns from this data is difficult. Current tools for mining structured data are inappropriate for free text. We outline problems involved in Knowledge Discovery in Text, and present an architecture for extracting patterns that hold across multiple documents. The capabilities that such a system could provide are illustrated.
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