Automatic document classification is of paramount importance to knowledge management in the information age. Document classification is a kind of text data mining and organization technique that automatically groups related documents into clusters. Most of the common techniques in document classification are based on the statistical analysis of a term, either word or phrase. Statistical analysi...

Text mining has been used for various purposes, such as document classification and extraction of domain-specific information from text. In this paper we present a study in which text mining methodology and algorithms were properly employed for academic dishonesty (cheating) detection and evaluation on open-ended college exams, based on document classification techniques. Firstly, we propose tw...

Text classification and feature selection plays an important role for correctly identifying the documents into particular category, due to the explosive growth of the textual information from the electronic digital documents as well as world wide web. In the text mining present challenge is to select important or relevant feature from large and vast amount of features in the data set. The aim o...

Text document is multifaceted object and associated with many properties such as multi labeledness. Under this a single text document can inherently belongs to more than one category simultaneously. Traditional single label and multi class text class ification paradigms cannot efficiently classify such multifaceted text corpus. Through our paper we are proposing a graph based frame work for Mul...

With the increase of information, document classification as one of the methods of text mining, plays vital role in many management and organizing information. Document classification is the process of assigning a document to one or more predefined category labels. Document classification includes different parts such as text processing, term selection, term weighting and final classification. ...

Automatic text classification is the problem of automatically assigning predefined categories to free text documents, thus allowing for less manual labors required by traditional classification methods. When we apply binary classification to multi-class classification for text classification, we usually use the one-against-the-rest method. In this method, if a document belongs to a particular c...

one of the complex documents in the real world is city maps. in these kinds of maps, text labels overlap by graphics with having a variety of fonts and styles in different orientations. usually, text and graphic colour is not predefined due to various map publishers. in most city maps, text and graphic lines form a single connected component. moreover, the common regions of text and graphic lin...

This paper presents a thesaurus-based approach to document classification. We define a classification space based on the notion of theme vectors. For a new text, we compute its characteristic vector by considering only a sample of randomly extracted lemmas. Then, we compute the differences between this vector and the vectors in the document model and the classification of the new text is decide...