An Ontology-based Framework for Text Mining

LDV Forum Pub Date : 2005-07-01 DOI:10.21248/jlcl.20.2005.70
Stephan Bloehdorn, P. Cimiano, A. Hotho, Steffen Staab
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引用次数: 63

Abstract

Structuring of text document knowledge frequently appears either by ontologies and metadata or by automatic (un-)unsupervised text categorization. This paper describes our integrated framework OTTO (OnTology-based Text mining framewOrk). OTTO uses text mining to learn the target ontology from text documents and uses then the same target ontology in order to improve the effectiveness of both supervised and unsupervised text categorization approaches.
基于本体的文本挖掘框架
文本文档知识的结构化通常是通过本体和元数据或自动(无)监督文本分类来实现的。本文描述了我们的集成框架OTTO(基于本体的文本挖掘框架)。OTTO使用文本挖掘从文本文档中学习目标本体,然后使用相同的目标本体,以提高监督和无监督文本分类方法的有效性。
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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