Automatic Text Classification is a semi-supervised machine learning task that automatically assigns a given document to a set of pre-defined categories based on its textual content and extracted features. Automatic Text Classification has important applications in content management, contextual search, opinion mining, product review analysis, spam filtering and text sentiment mining. This paper...

This paper presents Clustering Based Document classification and analysis of data. The proposed Clustering Based classification and analysis of data approach is based on Unsupervised and Supervised Document Classification. In this paper Unsupervised Document and Supervised Document Classification are used. In this approach Document collection, Text Preprocessing, Feature Selection, Indexing, Cl...

Text classification techniques mostly rely on single term analysis of the document data set, while more concepts especially the specific ones are usually conveyed by set of terms. To achieve more accurate text classifier, more informative feature including frequent co-occurring words in the same sentence and their weights are particularly important in such scenarios. In this paper, we propose a...

Support vector machines (SVMs) have been recognized as one of the most successful classification methods for many applications including text classification. Even though the learning ability and computational complexity of training in support vector machines may be independent of the dimension of the feature space, reducing computational complexity is an essential issue to efficiently handle a ...

The Vector Space Model (VSM) of text representation suffers a number of limitations for text classification. Firstly, the VSM is based on the Bag-Of-Words (BOW) assumption where terms from the indexing vocabulary are treated independently of one another. However, the expressiveness of natural language means that lexically different terms often have related or even identical meanings. Thus, fail...

Automated document classification can be a valuable tool for biomedical tasks that involve large amounts of text. However, in biomedicine, documents that have the desired properties are often rare, and special methods are usually required to address this issue. We propose and evaluate a method of classifying biomedical text documents, optimizing for utility when misclassification costs are high...

Huge amount data on the internet are in unstructured texts can‟t simply be used for further processing by computer , therefore specific processing method and algorithm require to extract useful pattern. Text mining is process to extract information from the unstructured data. Text classification is task of automatically sorting set of document into categories from predefined set. A major diffic...