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A Survey on Effective Classification for Text Mining using one-class SVM
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 65 - Number 23 |
| Year of Publication: 2013 |
| Authors: Safdar Sardar Khan, Divakar Singh |
10.5120/11227-6469
|
Safdar Sardar Khan, Divakar Singh . A Survey on Effective Classification for Text Mining using one-class SVM. International Journal of Computer Applications. 65, 23 ( March 2013), 35-39. DOI=10.5120/11227-6469
Abstract
Data mining techniques have been widely used to find new patterns and knowledge from large amount of data. While Bayesian models were widely used in the early days, more advanced machine learning methods, such as artificial neural networks and support vector machines, have been applied in recent years these techniques are used in different areas. The problem of text mining has gained increasing attention in recent years because of the large amounts of text data, which are created in a variety of social network, web, and other information-centric applications. Unstructured data is the easiest form of data which can be created in any application scenario. As a result, there has been a tremendous need to design methods and algorithms which can effectively process a wide variety of text applications. This paper will provide an overview of the different methods and algorithms which are common in the text domain, with a particular focus on mining methods.
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