Join Us Sign In

Knowledge Base Repository

In addition to research papers, the Design Society is developing several valuable resources for those interested in the study of design. These include a repository of PhD theses, a library of case studies and transcripts of design activities, and an archive of our newsletters. Please note that these resources are accessible exclusively to Design Society members.

Graph retrieval-augmented generation for enhancing LLM-based ML algorithm recommendation in product development

Sonntag, Sebastian; Dörnbach, Adrian; Nagarajah, Arun

Type:
Papers
DS 145: Proceedings of the DESIGN2026 19th International Design Conference
Year:
2026
Editor:
Štorga, M.; Škec, S.; Martinec, T.; Marjanović, D.; Pavković, N.
Author:
Sonntag, Sebastian; Dörnbach, Adrian; Nagarajah, Arun
Series:
DESIGN
Institution:
University of Duisburg-Essen, Germany
Page(s):
2551-2560
DOI number:
10.1017/pds.2026.10613
ISSN:
2732-527X (Online)
Abstract:
Recent advances in machine learning (ML) offer substantial potential for product development (PD), yet adoption remains limited. A crucial step is identifying suitable ML algorithms for a given PD problem, which requires translating domain-specific formulations into appropriate ML tasks. Prior work indicates that LLMs struggle with this step due to insufficient domain knowledge. Therefore, this study investigates whether a domain-specific GraphRAG approach improves model performance by enriching prompts with structured context from a PD knowledge graph.
Keywords:
artificial intelligence (AI), product development, large language model (LLM), machine learning, design engineering
DESIGN2026 - The 19th International Design Conference
Conferences

This site uses cookies and other tracking technologies to assist with navigation and your ability to provide feedback, analyse your use of our products and services, assist with our promotional and marketing efforts, and provide content from third parties. Privacy Policy.

Cookie Settings Accept Cookies