The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS
Transactions ID Number: 32-607
Full Name: Yi-Hsing Chang
Position: Associate Professor
Age: ON
Sex: Male
Address: 1 Nan-Tai St. Yung-Kang City Tainan Hsien, Taiwan, 710
Country: TAIWAN
Tel: 886-6-2533131 ext. 4336
Tel prefix:
Fax: 886-6-2541621
E-mail address: yhchang@mail.stut.edu.tw
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Title of the Paper: automatically constructing an effective domain ontology for document classification
Authors as they appear in the Paper: Yi-Hsing Chang
Email addresses of all the authors: yhchang@mail.stut.edu.tw
Number of paper pages: 10
Abstract: An effective domain ontology automatically constructed is proposed in this paper. The main concept is using the Formal Concept Analysis to automatically establish a domain ontology. Finally, the ontology is acted as the base for the Naïve 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 documents and testing documents respectively. In addition, the 10-fold cross validation is also applied to evaluate the performance of Naïve Bayes classifier. The F1-measure is as the assessment criteria. The experimental results show that the average F1-measure for 10 categories by Naïve Bayes classifier is 0.86. In the other hand, the average F1-measure is 0.88 by applying the 10-fold cross validation. Thus, the domain ontology automatically constructed could indeed act as the document ca!
tegories to reach the effectiveness for document classification.
Keywords: Naïve Bayes Classifier, Ontology, Formal Concept Analysis, Cross Validation, Document Classification
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