Text classification using Naive Bayes: An experiment to conference paper

• 主要作者: Sainin, Mohd Shamrie
• 格式: Conference or Workshop Item
• 語言: English
• 出版: 2005
• 主題: HD28 Management. Industrial Management
• 在線閱讀: http://repo.uum.edu.my/12432/1/ICOQSIA_shamrie.pdf; http://repo.uum.edu.my/12432/; http://lintas.uum.edu.my:8080/elmu/index.jsp?module=webopac-l&action=fullDisplayRetriever.jsp&szMaterialNo=0000332840

The basic text classification technique in forum application has been discussed in Sainin (2005a) and Sainin (2005b).The paper explains about the use of the basic naïve Bayes algorithm to classify forum text me ssages into two classes namely clean and bad. In the problem of document text classification for conference paper, various papers themes will normally be classified manually by the conference management.Once the classification of the papers is ready, the parallel sessions for presentation according to the themes will be scheduled. This process is time consuming and may classify papers into unrelated themes.Based on this situation, an automated text document classification can replace the manual classification; hence reduce the decision time.In this paper, the similar algorithm that was applied in the previous experiment for the forum messages classification will be discussed according to the experiment for conference paper classification.