基于本体的特征提取

C. Vicient, D. Sánchez, Antonio Moreno
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引用次数: 10

摘要

基于知识的数据挖掘和分类算法要求系统能够提取包含在原始文本文档中的文本属性,并将其映射到结构化的知识来源(如本体),以便对其进行语义分析。本文提出的系统以自动方式执行这些任务,依赖于预定义的本体,该本体陈述了其中的概念,后验数据分析将成为重点。作为功能,我们的系统侧重于从描述特定实体的文本资源中提取相关的命名实体。通过语言和基于web的共现分析来评估它们,将它们映射到本体论概念,从而发现对象的相关特征。该系统已经在旅游目的地和维基百科文本资源中进行了初步测试,显示出令人满意的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ontology-Based Feature Extraction
Knowledge-based data mining and classification algorithms require of systems that are able to extract textual attributes contained in raw text documents, and map them to structured knowledge sources (e.g. ontologies) so that they can be semantically analyzed. The system presented in this paper performs this tasks in an automatic way, relying on a predefined ontology which states the concepts in this the posterior data analysis will be focused. As features, our system focuses on extracting relevant Named Entities from textual resources describing a particular entity. Those are evaluated by means of linguistic and Web-based co-occurrence analyses to map them to ontological concepts, thereby discovering relevant features of the object. The system has been preliminary tested with tourist destinations and Wikipedia textual resources, showing promising results.
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