The motivation for this work arises from the need of Automatic Document Classification (ADC) which is necessary when the task involves business specific contexts which cannot be fulfilled via querying on any search engine. Since a large number of websites are available over the internet nowadays therefore users generally search information from different websites via search engines now. But search engines require appropriate keywords from users in order to give relevant information from the web and sometimes users have obtained irrelevant results if he or she is not sound enough to provide keywords correctly. Thus, we need a proper document classification for the material of our wish so that the one which is required can be obtained easily instead of wasting time in searching. To understand this, we have discussed the automatic document classification in news domain where we classify news articles into four distinct categories: business, science & technology, entertainment and health using Linear SVM with SGD training and multinomial NB classifier and compare their performance. The classification is based on the title of the news article taken as feature.

Automatic Document Classification, Linear SVM, Stochastic Gradient Descent, multinomial NB

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