Study on Clustering Computing Methods of Big Data

Abstract

In the past few years, the rapidly developing technology in the field of information technology is "big data". Clustering is one of the key tasks in a wide range of areas dealing with large amounts of data. This survey introduces various clustering methods used for effective big data clustering. Therefore, this review paper reviewed 15 research papers, which proposed various methods for effective big data clustering, such as k-means clustering, k-means variant clustering, fuzzy c-means clustering, possibility c-means clustering, collaborative filtering and optimization based clustering. In addition, detailed analysis is carried out by referring to the implementation tools used, the data sets used and the big data clustering framework adopted. Then, an effective solution must be developed to go beyond the existing technology to the special management of big data. Finally, the research problems and gaps of various big data clustering technologies are proposed to enable researchers to start with better big data clustering.