High-dimensional information is labeled through massive dimensions of structures,
disseminates advanced difficulties that to be understood in around all on its part these …

With the rapid development of big data, the scale, dimensions, diversity and sparsity of high-
dimensional data restrict the effectiveness of traditional clustering algorithms. This paper …

In this paper a new approach toward data processing is proposed that is inspired by all the
prominent data clustering algorithms proposed by scholars. The main motif that drove this …

Very large volumes of data analytics study the uncovering of hidden patterns, interplay, and
other discoveries. Today's technology enables data analyzing and obtaining answers …

There are some challenging issues in clustering problems and clustering methodologies,
which frequently attract researchers' interests. Ability of handling high dimensional feature …

With the rapid development of computer technology, the dimensions of data have exploded,
and many data analyses have become very difficult. To solve the above problems, the use of …

In the modern world, the widespread use of information and communication technology has
led to the accumulation of vast and diverse quantities of data, commonly known as Big Data …

Big Data processing systems handle huge unstructured and structured data to store,
process, and analyze through cluster analysis which helps in identifying unseen patterns to …

Clusters assessment is a major identified problem in big data clustering. Top big data
partitioning techniques, such as, spherical k-means, Mini-batch-k-means are widely used in …

The generation and development of big data has become a new, advanced and trending
information processing technology. In the era of cloud computing, we can obtain massive …