DocumentCode
2500085
Title
Comparison of Attribute Selection Methods for Web Texts Categorization
Author
Saian, Rizauddin ; Ku-Mahamud, Ku Ruhana
Author_Institution
Fakulti Sains Komputer dan Matematik, Univ. Teknol. MARA Perlis, Arau, Malaysia
fYear
2010
fDate
23-25 April 2010
Firstpage
115
Lastpage
118
Abstract
This paper presents a study on the performance of attribute selection methods to be used with Ant-Miner algorithm for web text categorization. The new generated data set by each attribute selection method was classified with Ant-Miner to see the performance in terms of predictive accuracy and the number of rules generated. The results of classification were also compared to C4.5 algorithm.
Keywords
Internet; data mining; pattern classification; text analysis; C4.5 algorithm; Web texts categorization; ant-miner algorithm; attribute selection methods; classification rules; Accuracy; Art; Computer networks; Data mining; Genetics; Information retrieval; Machine learning algorithms; Search methods; Text categorization; Web pages; attribute selection; classification; machine learning; web mining;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer and Network Technology (ICCNT), 2010 Second International Conference on
Conference_Location
Bangkok
Print_ISBN
978-0-7695-4042-9
Electronic_ISBN
978-1-4244-6962-8
Type
conf
DOI
10.1109/ICCNT.2010.13
Filename
5474523
Link To Document