An Optimization of Multi-Class Document Classification with Computational Search Policy

Main Article Content

Somchai - Limsiroratana, Lecturer


In the era of internet communication, many electronic documents are spread and flow on the platform of website in every splits of seconds. The research interest for the process of knowledge discovery is changed from the traditional data to online data such as online news document classification. Most percentage of the online data is text document and therefore the optimization of multi-class document classification is becoming a challenge for today society. Traditional search policy for feature selection process is degrading with exhaustive search for complex feature in document classification. Therefore, meta-heuristic based computational search is also becoming good solution to overcome the problem of exhaustive search with exploitation process. The search policy of computational algorithm can provide the global optimal solution with random search approach on both exploitation and exploration process, and the selected search results of feature subsets can support the optimal classification results.

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How to Cite
K. S. KYAW and S.- Limsiroratana, “An Optimization of Multi-Class Document Classification with Computational Search Policy”, ECTI-CIT, vol. 14, no. 2, pp. 149-161, Jun. 2020.
Research Article
Author Biography

Somchai - Limsiroratana, Lecturer, Department of Computer Engineering, Prince of Songkla University, Thailand

Somchai LIMSIRORATANA was born in southern Thailand. He received B.Eng. degree in electrical engineering from Prince of Songkla University in 1991, M.Arg and Dr.Arg degrees with the research topic about the detection of fruits on natural background research, from division of environmental science and technology, Kyoto University in 2000 and 2005 respectively. He has been working as lecturer at Department of Computer Engineering, Prince of Songkla University since 1991. His research interests are agricultural image processing, medical image processing, digital watermarking, office automation, content management , Data Mining and AI.



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