An intelligent artificial intelligence framework for business insight generation from streaming data
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.
Keywords
Champion model; Gini coefficient; Machine learning pipeline; Natural language processing techniques; Receiver operating characteristic curve; Streaming data
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PDFDOI: http://doi.org/10.11591/ijai.v15.i5.pp4071-4080
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Copyright (c) 2026 Benymol Jose, Sajimon Abraham, Nikitha Sajith

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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938
This journal is published by the Institute of Advanced Engineering and Science (IAES).