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Automatically Constructing an Effective Domain Ontology for Document Classification 被引量:2

Automatically Constructing an Effective Domain Ontology for Document Classification
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摘要 An effective domain ontology automatically constructed is proposed in this paper. The main concept is using the Formal Concept Analysis to automatically establish domain ontology. Finally, the ontology is acted as the base for the Naive Bayes classifier to approve the effectiveness of the domain ontology for document classification. The 1752 documents divided into 10 categories are used to assess the effectiveness of the ontology, where 1252 and 500 documents are the training and testing documents, respectively. The Fl-measure is as the assessment criteria and the following three results are obtained. The average recall of Naive Bayes classifier is 0.94. Therefore, in recall, the performance of Naive Bayes classifier is excellent based on the automatically constructed ontology. The average precision of Naive Bayes classifier is 0.81. Therefore, in precision, the performance of Naive Bayes classifier is gored based on the automatically constructed ontology. The average Fl-measure for 10 categories by Naive Bayes classifier is 0.86. Therefore, the performance of Naive Bayes classifier is effective based on the automatically constructed ontology in the point of F 1-measure. Thus, the domain ontology automatically constructed could indeed be acted as the document categories to reach the effectiveness for document classification.
出处 《Computer Technology and Application》 2011年第3期182-189,共8页 计算机技术与应用(英文版)
关键词 Naive bayes classifier ONTOLOGY formal concept analysis document classification. 领域本体 文档分类 朴素贝叶斯分类器 文件分类 自动构造 形式概念分析 平均精度 测量点
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