Computational intelligence based sustainable computing with classification model for big data visualization on map reduce environment

Classification Algorithms for Big Data Analysis, a Map Reduce Approach

Since many years ago, the scientific community is concerned about how to increase the accuracy of different classification methods, and major achievements have been made so far. Besides this issue, the increasing amount of data that is being generated every day by remote sensors raises more challenges to be overcome. In this work, a tool within the scope of InterIMAGE Cloud Platform (ICP), whic...

Big Data Processing with Hadoop Map-reduce

The amount of data in our world has been exploding, and analyzing large data sets—so-called big data—will become a key basis of competition, underpinning new waves of productivity growth, innovation, and consumer surplus. The increasing volume and detail of information captured by enterprises, the rise of multimedia, social media, and the Internet of Things will fuel exponential growth in data ...

Computational Intelligence for Big Social Data Analysis

Implementation of image processing system using handover technique with map reduce based on big data in the cloud environment

Cloud computing is the one of the emerging techniques to process the big data. Cloud computing is also, known as service on demand. Large set or large volume of data is known as big data. Processing big data (MRI images and DICOM images) normally takes more time. Hard tasks such as handling big data can be solved by using the concepts of hadoop. Enhancing the hadoop concept will help the user t...

KSRS : Keyword - based Service Recommendation System for Shopping using Map - Reduce on Hadoop for Big Data

Service recommender systems are important tools for giving appropriate recommendations to users. From many years, the amount of customers, services provided to them a n d online information is growing rapidly, i t motivates for service recommender system. The traditional service recommender systems has limitations of scalability and inefficiency when analyzing or processing such large amount of...