Document Clustering Approach Using R Programming with Feedback Data
1Dr. Venkata Reddy Medikonda, Dr. Uma Pavan Kumar Kethavarapu
The current day needs of the information technology are based on huge amount of data storage and processing. After storing and processing of such huge amounts of the data such as banking, retail, manufacturing and medical data the fundamental requirement is to analyse that data and getting interesting patterns so as to observe the pulse of the stake holders and identify the challenges to reach the customers or members according to the results of the analysis.The analytics playing a key roleto cater the needs of the various stakeholders andyielding more profits to the companies. The context of analytics can be observed in business point of view and as well as machine learning, data science regards. The current work explains the usage of clustering with R programming packages and methods. Clustering is an unsupervised learning which generates the various clusters for the given data set. A cluster conceptually gives a group of similar data items when compared with other cluster gives opposite properties. In machine learning clustering algorithm plays a vital role in many usecases.The current work considers the source as some document and applying various clustering methods so as to pre-process the given document without unnecessary data. The outcome work is various clusters after processing unnecessary input data from the given input data.
Clustering, Document clustering, term matrix, analytics, Machine Learning