Automated Text Document Classification Using Predictive Network

B. Y. Baravkar

Abstract: Every day the mass of information available, merely finding the relevant information is not the only task of automatic text classification systems. Instead the automatic text classification systems are supposed to retrieve the relevant information as well as organize according to its degree of relevancy with the given query. The main problem in organizing is to classify which documents are relevant and which are irrelevant. The Automated text classification consists of automatically organizing clustered data. We propose an automatic method of text classification using machine learning based on the disambiguation of the meaning of the word we use the word net word embedding algorithm to eliminate the ambiguity of words so that each word is replaced by its meaning in context. The closest ancestors of the senses of all the undamaged words in a given document are selected as classes for the specified document.

Keywords: Descriptive clustering, feature selection, logistic regression, model selection, machine learning