2024-03-29T00:52:32Z
https://meral.edu.mm/oai
oai:meral.edu.mm:recid/4212
2021-12-13T04:40:56Z
1582963302567:1597824273898
user-ucsy
Multi-category Classification of Web Pages by using Random Forest Classifier
Aung, Win Thanda
Nyunt, Thi Thi Soe
To classify Web objects into predefined semanticstructure is called the Web Page classification. Oneof the most essential technique for Web Mining isthe automatic web page classification given that theweb is a huge repository of various informationincluding images, videos etc. And there is a need forcategorization web pages to satisfy user needs. Theclassification of web pages into each categoryexclusively relies on man power which cost muchtime and effort. To alleviate this manuallyclassification problem, more researchers focus onthe issue of web pages classification technology. Inthis paper, we proposed Random Forest Classifier(RF) based on random forest method for multicategoryweb page classification. The proposed RFclassifier can classify web pages efficientlyaccording to their corresponding class without usingother feature selection methods. We compared theaccuracy of the proposed approach to decision treeclassifier using in the same Yahoo web pages. Theexperiments have shown that the proposed approachis suitable for the multi-category web pageclassification.
2009-12-30
http://hdl.handle.net/20.500.12678/0000004212
https://meral.edu.mm/records/4212