Social Networking Unstructured Big Data Clustering using K-Means on R
Seema Jangid, Reshu Grover, Pratap Singh Patwal · Zenodo (CERN European Organization for Nuclear Research) · 2021
The main goal of this paper is to describe the implementation of an out of core techniques for the data analysis of very large social networking dataset with the sequential and parallel version of the clustering algorithms. To evaluate the performance of clustering algorithm such as k means and hierarchical algorithm on social media data sets using spark frame work with R programming on cloudera. The implementation purpose we have used social media Youtube dataset, which collected from UCI machine repository. To compare the algorithm to give an exact result this states the benchmark and time consideration to solve a problem. Our main aim, therefore, the mining and clustering unstructured large volume data and Test and comparison of the results for different clustering algorithm.