Cloud computing is standard services of delivering storage, databases, applications, on-demand basis, etc. Cloud computing provides centralized data storage that is commonly maintained in a remote server, which contains a large amount of data in the form of files and documents. By storing similar document and files in a centralized server, the storage space contains duplicate data, and it creates memory consumption problems. To resolve this issue, we propose a smart cloud data management using Frequent Semantic Correlation Analysis (FSCA) method based on Conceptual-Semantic Relational Distributed Clustering (CSRDC). The proposed method uses the Euclidian vector space summarization measure to create a new document after deleting the unwanted contents and by merging related documents from historical document terms. This implementation saves the original information specified, valid points of key terms even from lower priority and older documents. This will also free up space by deleting the unwanted sentences to reduce the memory consumption and delete the unwanted file from the duplicate index.
Volume 11 | Issue 5
Pages: 15-24