This survey paper, mainly focused on challenges of big data, how to extract the required data from large volume of data, and also various clustering algorithm. For the extraction of data, mapreduce function is used which is mainly used in Google search engine....
The current era of Big Data [1], [2], [3] has forced both researchers and industries to rethink the computational solutions for getting useful insight on massive data produced in a wide variety of real life scenarios. In fact, a great deal of attention has been devoted to the design of...
Although the tight clustering method is an intelligent algorithm that provides a reliable outcome in gene clustering, it fails to incorporate huge data of tens of thousands of gene expressions. These huge data sets, which are results of advances in biomedical imaging technologies and gene mapping te...
Clustering has primarily been used as an analytical technique to group unlabeled data for extracting meaningful information. The fact that no clustering algorithm can solve all clustering problems has resulted in the development of several clustering algorithms with diverse applications. We review data clu...
It shows the outstanding role of clustering in various disciplines, such as education, marketing, medicine, biology, and bioinformatics. It also discusses the application of clustering to different fields attracting intensive efforts among the scientific community, such as big data, artificial ...
Big data analytics, which studies large amounts of data of various types to disclose hidden patterns, is attracting more and more attention in both academic and industrial areas. One of the most significant problem of big data analytics is the task of clustering analysis, which is to group sim...
In addition to the metaheuristic algorithm, the primary goal of the data mining process is to gather data from a big data set. The data can then be translated into a clear format for further usage. Clustering is a popular experimental data analysis tool. Objects are arranged using clustering ...
It’s not a bad time to be a Data Scientist. Serious people may find interest in you if you turn the conversation towards “Big Data”, and the rest of the party crowd will be intrigued when you mention “Artificial Intelligence” and “Machine Learning”. EvenGoogle thinksyou’re not ba...
in 2019, and he obtained his Bachelor of Engineering degree from Nanyang Technological University in 2014. Dr. Zhang's research is centered around the design of database systems and big data processing frameworks optimized for ...
Such algorithms are ideal for the recovery of big clusters and compact clusters. • Divisive algorithms: These algorithms work in the opposite direction; that is, at each stage they generate a clustering sequence of m. The clustering is created by dividing a single cluster into two results ...