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Comparison of IR Models for Text Classification
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 61 - Number 22 |
| Year of Publication: 2013 |
| Authors: Priyanka Desai, G. R. Kulkarni |
10.5120/10228-4713
|
Priyanka Desai, G. R. Kulkarni . Comparison of IR Models for Text Classification. International Journal of Computer Applications. 61, 22 ( January 2013), 20-25. DOI=10.5120/10228-4713
Abstract
As there is availability of large amount of data on the web, but due to constraints web is only used for browsing and searching. Traditional IE uses NLP techniques such as lexicons, grammars, whereas web applies machine learning and pattern mining techniques to exploit the syntactical patterns or layout structures of the template-based documents. Information Retrieval is the art of presentation, storage, organization of and access to information items. IR now–-days mainly deals with retrieving information based on user queries. The paper deals with basic understanding of IR and IR models and shows Support Vector Machines is a good technique fir classification of huge data sets.
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