Text mining: Challenges and future directions

A., Akilan M. Sc, M. Phil
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引用次数: 35

Abstract

In today's world, the amount of stored information has been enormously increasing day by day which is generally in the unstructured form and cannot be used for any processing to extract useful information, so several techniques such as summarization, classification, clustering, information extraction and visualization are available for the same which comes under the category of text mining. Text Mining can be defined as a technique which is used to extract interesting information or knowledge from the text documents. Text mining, also known as text data mining or knowledge discovery from textual databases, refers to the process of extracting interesting and non-trivial patterns or knowledge from text documents. Regarded by many as the next wave of knowledge discovery, text mining has very high commercial values.
文本挖掘:挑战与未来方向
当今世界,存储的信息量日益急剧增加,而这些信息通常以非结构化的形式存在,无法进行任何处理来提取有用的信息,因此在文本挖掘的范畴内,有摘要、分类、聚类、信息提取和可视化等技术可供使用。文本挖掘可以定义为一种从文本文档中提取有趣信息或知识的技术。文本挖掘,也称为文本数据挖掘或从文本数据库中发现知识,是指从文本文档中提取有趣的和重要的模式或知识的过程。文本挖掘被许多人视为下一波知识发现,具有很高的商业价值。
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