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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Nikitha Sajith
LTM Limited
Computer Science & IT Engineering

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An intelligent artificial intelligence framework for business insight generation from streaming data Benymol Jose; Sajimon Abraham; Nikitha Sajith
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 5: October 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i5.pp4071-4080

Abstract

Big data analytics helps organizations leverage their data to uncover new opportunities, leading to smarter decisions, more efficient operations, and ultimately higher profits. Effective use of big data and creating important predictive models make it more straightforward for a business to realize what the consumer likes and what he or she does not. This will enable the business to propose better offers and administrations with their items when contrasted to its competitors. In this paper, the authors suggest the use of a big data analytics platform combined with natural language processing (NLP) techniques to do the intelligent processing of unstructured streaming data. A new method utilizing Apache Spark pipelining is proposed to achieve predictive analytics for unstructured data streams. With this predictive model, mining of the unstructured streaming data can be done and intelligent predictions are made possible in real time using artificial intelligence techniques.
Co-Authors Benymol Jose Sajimon Abraham