Comparative Study on Various Text Mining Algorithms in Data Mining
Keywords:
Text mining, Data mining, WEKA, UCI repository, AlgorithmsAbstract
This paper describes about text mining from the source of data mining. Data mining is nothing but an extraction of hidden knowledge from the huge database. There are lot of domains in data mining as text mining, image mining, sequential pattern mining, web mining and so. Here text mining can be used for extracting the information of the text using various algorithms using data mining software called WEKA. The data sets are taken from the UCI repository for performing the text mining techniques.
References
- Abdullah Wahbeh H, Mohammed Al-Kabi., “Comparative Assessment of the Performance of Three WEKA Text Classifiers Applied to Arabic Text”, Vol. 21, No. 1, pp. 15- 28, 2012.
- Abdullah Wahbeh H, Qasem Al-Radaideh A, Mohammed Al-Kabi N, and Emad Al-ShawakfaM., “A Comparison Study between Data Mining Tools over some Classification Methods”.
- Artur Ferreira., “Survey on Boosting Algorithms for Supervised and Semi-supervised Learning”.
- Christophe Giraud-Carrier., “Meta learning - A Tutorial”.
- ChristophGoller, Joachim Löning., Thilo Will, Werner Wolff., “Automatic Document Classification: A thorough Evaluation of various Methods”.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRCSEIT
This work is licensed under a Creative Commons Attribution 4.0 International License.