This paper explores hybrid approaches integrating rule-based systems and Large Language Models (LLMs) for generating actionable business insights from complex datasets. It addresses the limitations of traditional rule-based systems and standalone LLMs, proposing a solution that combines their respective strengths for enhanced data extraction and insight generation.
Publisher
Published On
Authors
Aliaksei Vertsel, Mikhail Rumiantsau
Tags
rule-based systems
Large Language Models
business insights
data extraction
hybrid approaches
actionable insights
complex datasets
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