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Massive volumes of data are generated by various users, entities, applications and disseminated online. This copious volume of big data is distributed across millions of websites and is available for various applications. Search engines do provide a simple mechanism to access this data. Accessing this data using search engines requires a user to spend time and resources to manually click and download...
Evolution of Big Data have made giant organizations to embrace data analytics as one of its life line processes. Results from big data analytics have undoubtedly proved that it can bring high productivity in organizations. But several studies also confirms that, there exists many difficulties in handling big data. One of the most acclaimed problem in big data analytics is mining the most frequent...
The rapid increase in population creates an issue in handling and analyzing the population data for the traditional data base management system. So Big data came into figure to solve the issue. The main components of Big data are Hadoop and Map-Reduce. Big data is more efficient in comparison to the traditional data base system due to some of its basic features like Velocity, Veracity, Volume, Verity...
Now a days people are enjoying the world of data because size and amount of the data has tremendously increased which acts like an invitation to Big data. But some of the classifier techniques like Support Vector Machine (SVM) is not able to handle the huge amount of data due to it's excessive memory requirement and unreasonable complexity in algorithm tough it is one of the most popularly used classifier...
Research and implementation of big data analytics is a booming area with huge latent to give valuable insights in the areas of healthcare and lifescience. While there are many challenges with implementation of big data analytics in its implementation. The major challenges of big data analytics are 3Vs (Volume, Velocity, and Variety), makes it difficult to implement it for clinical applications. However,...
Big data is a term that defines data set are so large or complex that traditional data processing applications are inadequate. It is also defined by the 3V's i.e. Volume, Velocity and Variety. By volume we mean the enormous amount of data that the organizations collect from variety of sources. Velocity here stands for unprecedented speed via which the data streams in and needs to be handled within...
Generally, the medical datasets are heterogeneous and large dimensional that contains a million of patient records. Extracting information from such datasets is a tedious process, which can be made easier by some of the clustering algorithms available in data mining. In this paper, three clustering algorithms such as Medical Storage Platform for data Mining (MSPM), Homogeneity Similarity based Hierarchical...
Huge losses occur all most on a daily basis due to many natural calamities like earth quakes, storms, cyclones etc. that will have adverse effects on the lives of billions of people. In the modern world, the prediction of environmental impact had become a challenging task. A rigorous rainfall prediction system is very useful and important for most of the country like India, because these are mainly...
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