Integrating KGs and ontologies with RAG for personalised summarisation in regulatory compliance.
Year: 2024
Type: conference-paper
Abstract: With the growing complexity and increased volumes, regulatory texts are fast becoming a significant challenge for organisations to remain compliant. Traditional ways of summarising legal texts need to be more accommodating of critical, domain-specific requirements, rendering the process ultimately inefficient and subject to the risk of noncompliance. Therefore, this paper proposes a new solution integrating Ontology and Knowledge Graphs (KGs) with the Retrieval-Augmented Generation (RAG) paradigm to aid process automation and improve regulatory compliance. It offers deep semantic understanding, accurate contextual summaries, and personalised insights relevant to users' needs. In the meantime, this will assist organisations in operating with more precision and confidence in an ever-changing regulatory environment.
Authors: Arshad, Umair, Corsar, David, Nkisi-Orji, Ikechukwu
Institution: Robert Gordon University
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7082313076
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