A Brief Survey of Text Mining

A. Hotho, A. Nürnberger, G. Paass
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引用次数: 913

Abstract

The enormous amount of information stored in unstructured texts cannot simply be used for further processing by computers, which typically handle text as simple sequences of character strings. Therefore, specific (pre-)processing methods and algorithms are required in order to extract useful patterns. Text mining refers generally to the process of extracting interesting information and knowledge from unstructured text. In this article, we discuss text mining as a young and interdisciplinary field in the intersection of the related areas information retrieval, machine learning, statistics, computational linguistics and especially data mining. We describe the main analysis tasks preprocessing, classification, clustering, information extraction and visualization. In addition, we briefly discuss a number of successful applications of text mining.
文本挖掘概述
存储在非结构化文本中的大量信息不能简单地用于计算机的进一步处理,计算机通常将文本作为简单的字符串序列处理。因此,需要特定的预处理方法和算法来提取有用的模式。文本挖掘一般是指从非结构化文本中提取有趣信息和知识的过程。在这篇文章中,我们讨论文本挖掘作为一个年轻的跨学科领域,在相关领域的交叉信息检索,机器学习,统计学,计算语言学,特别是数据挖掘。描述了主要的分析任务:预处理、分类、聚类、信息提取和可视化。此外,我们还简要讨论了文本挖掘的一些成功应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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