With the dramatic increase in the amount of content available in digital forms gives rise to a problem to manage this online textual data. As a result, it has become a necessary to classify large texts (documents) into specific classes. And Text Classification is a text mining technique which is used to classify the text documents into predefined classes. Most text classification techniques wor...

We investigate the following problem: Given a set of documents of a particular topic or class P , and a large set M of mixed documents that contains documents from class P and other types of documents, identify the documents from class P in M . The key feature of this problem is that there is no labeled nonP document, which makes traditional machine learning techniques inapplicable, as they all...

Text mining is variance of a field called data mining. To make unstructured data workable by the computer Text mining is used which is also referred as “Text Analytics”. Text categorization, also called as topic spotting is the task of automatically classifies a set of documents into groups from a predefined set. Text classification is an essential application and research topic because of incr...

When we apply binary classification to multi-class classification for text classification, we use the One-Against-All method generally. However, this One-Against-All method has a problem. That is, the documents of a negative set are not labeled manually while those of a positive set are labeled by human. In this paper, we propose that the Sliding Window technique and the EM algorithm are applie...

In this paper we present Document analysis and classification system to segment and classify contents of Arabic document images. This system includes preprocessing, document segmentation, feature extraction and document classification. A document image is enhanced in the preprocessing by removing noise, binarization, and detecting and correcting image skew. In document segmentation, an algorith...

Nowadays, the automated text classification has witnessed special importance due to the increasing availability of documents in digital form and ensuing need to organize them. Although this problem is in the Information Retrieval (IR) field, the dominant approach is based on machine learning techniques. Approaches based on classifier committees have shown a better performance than the others. I...

This paper exposes the results of our participation in the Document Mining track at INEX’07. We have focused on the task of classification of XML documents. Our approach to deal with structured document representations uses classification methods for plain text, applied to flattened versions of the documents, where some of their structural properties have been translated to plain text. We have ...

Automatic classification of text documents has become an important research issue now days. Proper classification of text documents requires information retrieval, machine learning and Natural language processing (NLP) techniques. Our aim is to focus on important approaches to automatic text classification based on machine learning techniques viz. supervised, unsupervised and semi supervised. I...