Published Paper Details:

Machine learning is an Artificial Intelligent (AI) that furnishes systems with the capability to automatically learn and improve from past experience and historical data. The primary aim is to authorize the computers learn automatically without human involvement and adjust actions accordingly. The concept of clustering plays a supplemental challenge to existing learning algorithm. The proposed system works based on the multi-view clustering. One crucial problem in telecommunication is that today data is sizable, dynamic and heterogeneous. Multi-view clustering is the unsupervised machine learning technique which is used to collect data from multiple domains and increases the data security, and encoding to optimize the storage size. Rather than this implementation, we introduce a new exclusive model to segregate the data through some categories using k-means algorithm. The experiment shows that our method is effective in storage optimization and identifies the best using clustering.