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 recent developments in the modern data collection tools, techniques, and storage
capabilities are leading towards huge volume of data. The dimensions of data indicate the …

In this paper a data mining approach for classification of stocks into clusters is presented.
After classification, the stocks could be selected from these groups for building a portfolio. It …

Customers increasingly use various social media to share their opinion about restaurants
service quality. Big data collected from social media provides a data platform to improve the …

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 …

The data clustering with automatic program such as k-means has been a popular technique
widely used in many general applications. Two interesting sub-activity of clustering process …

Purpose: This study sought to review the characteristics, strengths, weaknesses variants,
applications areas and data types applied on the various Dimension Reduction techniques …

This paper presents the implementation of a new text document classification framework that
uses the Support Vector Machine (SVM) approach in the training phase and the Euclidean …

Text Categorization is a pattern classification task for text mining and necessary for efficient
management of textual information systems. The documents can be classified by three ways …

Many studies on developing technologies have been published as articles, papers, or
patents. We use and analyze these documents to find scientific and technological trends. In …