基于SUMO和WordNet本体集成的文本分类模型研究

doi:10.11925/infotech.1003-3513.2011.01.05

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摘要

针对传统文本分类方法和目前语义分类方法中存在的问题,提出基于SUMO和WordNet本体集成的文本分类模型,该模型利用WordNet同义词集与SUMO本体概念之间的映射关系,将文档-词向量空间中的词条映射成本体中相应的概念,形成文档-概念向量空间进行文本自动分类。实验表明,该方法能够极大降低向量空间维度,提高文本分类性能。

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	胡泽文
	王效岳
	白如江

关键词 ： SUMO本体, WordNet, 本体集成, 文本分类模型, 词向量空间, 概念向量空间

Abstract：

Aiming at the existing problems in the traditional text classification methods and the current semantic classification methods, a new text classification model based on SUMO and WordNet Ontology integration is proposed. This model utilizes the mapping relations between WordNet synsets and SUMO Ontology concepts to map terms in document-words vector space into the corresponding concepts in Ontology, and forms document-concepts vector space to classify texts automatically. The experiment results show that the proposed method can greatly decrease the dimensionality of vector space and improve the text classification performance.

Key words： SUMO Ontology WordNet Ontology integration Text classification model Word vector space Concept vector space

收稿日期: 2010-11-02

G250 TP391

基金资助:

本文系国家社会科学基金一般项目“海量网络学术文献自动分类研究”(项目编号:10BTQ047)和教育部人文社会科学研究规划一般项目“基于本体集成的文本分类关键技术研究”(项目编号:09YJA870019)的研究成果之一。

引用本文:

胡泽文, 王效岳, 白如江. 基于SUMO和WordNet本体集成的文本分类模型研究[J]. 现代图书情报技术, 2011, 27(1): 31-38.
Hu Zewen, Wang Xiaoyue, Bai Rujiang. Study on Text Classification Model Based on SUMO and WordNet Ontology Integration. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2011.01.05.

链接本文:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2011.01.05

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