Enhancing decision making through similarity-driven knowledge integration in resource allocation and content matching.

Jayawardena, Lasal

Abstract

This research aims to build a novel framework that enhances decision-making through an integration of similarity driven Case-Based Reasoning (CBR) with advanced Large Language Model (LLM) techniques via Retrieval Augmented Generation (RAG) and Genetic Algorithm (GA) optimisation. Currently, experimental work focuses on refining the loss function components to tune angle-optimised embedding models using both semi-supervised and unsupervised approaches. In parallel, experiments are being conducted to fine-tune LLMs as baselines for evaluation and to determine the best way to use LLMs as evaluative judges. Preliminary data analysis and enrichment have been conducted on operational datasets (e.g., WM Nicol company records). The final goal is to advance the state-of-the-art in CBR methods while providing a robust foundation for adaptive, context-aware decision support across multiple domains.

Citation

JAYAWARDENA, L. 2025. Enhancing decision making through similarity-driven knowledge integration in resource allocation and content matching. In Martin, K. and Ye, X. (eds.) ICCBR-WS 2025: joint proceedings of the workshops and doctoral consortium at the 33rd International conference on case-based reasoning (ICCBR-WS 2025) co-located with the 33rd International conference on case-based reasoning (ICCBR 2025), 30 June 2025, Biarritz, France. CEUR workshop proceedings, 3993. Aachen: CEUR-WS [online], pages 90-94. Available from: https://ceur-ws.org/Vol-3993/short7.pdf

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 33rd International conference on case-based reasoning workshops and doctoral consortium (ICCBR-WS 2025) co-located with the 33rd International conference on case-based reasoning (ICCBR 2025)
• Start Date: Jun 30, 2025
• Acceptance Date: Apr 6, 2025
• Online Publication Date: Jun 12, 2025
• Publication Date: Jul 8, 2025
• Deposit Date: Jul 31, 2025
• Publicly Available Date: Jul 31, 2025
• Publisher: CEUR-WS
• Peer Reviewed: Peer Reviewed
• Pages: 90-94
• Series Title: CEUR-workshop proceedings
• Series Number: 3993
• Series ISSN: 1613-0073
• Book Title: ICCBR-WS 2025
• Keywords: Case-based reasoning; Large language models; Retrieval augmented generation; Genetic algorithms; Embedding models
• Public URL: https://rgu-repository.worktribe.com/output/2941425
• Publisher URL: https://ceur-ws.org/Vol-3993/