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  1. University of Computer Studies, Yangon
  2. Conferences

Categorization of computer science papers using random forest

http://hdl.handle.net/20.500.12678/0000005059
809bdd47-831b-4dbc-aec7-93ba44b8cf39
05905367-6747-44bb-a6df-5612f46ed9fc
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54_PDFsam_PSC_final 54_PDFsam_PSC_final proof.pdf (137 Kb)
Publication type Article
Upload type Publication
Title
Categorization of computer science papers using random forest
en
Publication date 2017-12-27
Authors
Oo, Zin Mar
Description
Automatic categorization of text documentis difficult and time consuming. This thesisproposed a method for automatic categorizationof computer science paper using random forestclassifier. Decision trees are widely used for thetext categorization task and random forest offersthe high accuracy and due to the nature ofrandom forest, it is suitable for the task of textcategorization.Random forest used differenttraining dataset and random split at each nodefor the construction of decision forest.Usingrandom forest can provide high accuracy incategorization of text documents.The system willbe implemented using C# programming languageMS SQL server 2005. Computer sciences paperfrom IEEE conferences will be collected andtrained using the random forest. Trained randomforest will be stored using C# serializationtechnique in hard disk. Stored random forest canbe used to classify the incoming conference paperinto their associated category. The proposedsystem will compute the accuracy on the testdataset using hold-out method and will comparethe accuracy with decision tree (C4.5) algorithm.
Journal articles
Eighth Local Conference on Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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