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  1. University of Computer Studies, Yangon
  2. Faculty of Computer Science

Classification of Web pages using TF-IDF and Ant Colony Optimization

http://hdl.handle.net/20.500.12678/0000004271
http://hdl.handle.net/20.500.12678/0000004271
b3a40a7a-fda3-4db2-b394-219bba883e0c
6fb4bf21-ed9c-43a3-8c25-aec8d7895ddc
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Publication
Title
Title Classification of Web pages using TF-IDF and Ant Colony Optimization
Language en
Publication date 2014-12
Authors
San, Pan Ei
Aye, Nilar
Description
In this paper we describe the new classification algorithm for web page classification is ant colony optimizationalgorithm. The algorithm’s aim is to solve for discrete problem and discreteness of text documents’ features. In this paper, thesystem consists two parts for classification: training processing and classifying processing. In training process, the systemremoves the unnecessary part of the web page in preprocessing step. After preprocessing step, each text is represented by vectorspace model using TF-IDF formula. In the classifying process, the testing web page is tested to classify appropriated class labelby ant colony algorithm and ant colony algorithm works to find the optimal path or optimal class for text features by matchingduring iteration in the algorithm. The satisfactory accuracy of classification can be getting in this system.
Keywords
Ant Colony Optimization (ACO)
Identifier 2319- 8885
Journal articles
International Journal of Scientific Engineering and Technology Research(IJSERT)
Conference papers
Books/reports/chapters
Thesis/dissertations
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