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Hybrid LLM/Rule-based Approaches to Business Insights Generation from Structured Data

Business

Hybrid LLM/Rule-based Approaches to Business Insights Generation from Structured Data

A. Vertsel and M. Rumiantsau

Discover how Aliaksei Vertsel and Mikhail Rumiantsau explore a groundbreaking hybrid approach that fuses rule-based systems with Large Language Models to enhance data extraction and generate actionable business insights. This innovative research addresses the adaptability of traditional methods and the precision of LLMs, creating a powerful synergy for better decision-making.

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Playback language: English
Abstract
This paper explores hybrid approaches integrating rule-based systems and Large Language Models (LLMs) for generating actionable business insights. Traditional rule-based systems lack adaptability, while LLMs, though powerful, can lack precision. The hybrid approach aims to combine the strengths of both, improving data extraction and insight generation.
Publisher
Published On
Authors
Aliaksei Vertsel, Mikhail Rumiantsau
Tags
hybrid approaches
rule-based systems
Large Language Models
business insights
data extraction
adaptability
precision

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