It is a task to turn unseen, unstructured and time-sensitive computer data into data for decision making. Today’s available instruments manage only structured data. Without knowing its potential importance and use, all the transaction data is collected. It contributes to other issues related to big data analytics in storage, archiving, processing, not giving the business consumer valuable business insights. We are proposing a context-aware pattern approach in this paper to filter specific transaction data based on company preference. This system will reduce the complexity and expense of data processing such as storage, archiving, backup, recovery, etc.
Author (s) Details
Department of Computer Science Engineering, Sri Muthukumaran Institute of Technology, Chennai, India.
Assistant Professor P. E. Rubini
Department of Computer Science and Engineering, CMR institute of Technology, Bengaluru, India.
Dr. V. Sellam
Department of Computer Science Engineering, SRM University, Chennai, India.
Dr. S. Venkata Lakshmi
Department of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India.
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