Document classification is a growing interest in the research of text mining. Correctly
identifying the documents into particular category is still presenting challenge because of …

The majority of the data is preserved as text (about 75%), hence It is believed that text
mining has a significant commercial potential. Unstructured texts continue to be the most …

While naive Bayes is quite effective in various data mining tasks, it shows a disappointing
result in the automatic text classification problem. Based on the observation of naive Bayes …

With the proliferation of unstructured data, text classification or text categorization has found
many applications in topic classification, sentiment analysis, authorship identification, spam …

In this contemporaneous world, it is an obligation for any organization working with
documents to end up with the insipid task of classifying truckload of documents, which is the …

Text classification is a very important area in information retrieval. Text classification
techniques used to classify documents into a set of predefined categories. There are several …

This work implements an enhanced hybrid classification method through the utilization of the
naïve Bayes classifier and the Support Vector Machine (SVM). In this project, the Bayes …

Naïve Bayes classifiers which are widely used for text classification in machine learning are
based on the conditional probability of features belonging to a class, which the features are …

With the increasing availability of electronic documents and the rapid growth of the World
Wide Web, the task of automatic categorization of documents became the key method for …

The exponential growth of the internet has led to a great deal of interest in developing useful
and efficient tools and software to assist users in searching the Web. Document retrieval …