A new scientific paper titled “Premium Domain Name Recommendation via Semantic Retrieval and Reranking of Fixed Aftermarket Inventories” has been published in the international journal IEEE Access. The research was conducted by Milutin Pavićević, Tomo Popović, Srđan Krčo, and Miodrag Vujković from the University of Donja Gorica (UDG) and DunavNET.
The study addresses the challenge of recommending relevant premium domain names from large collections of domains already available for resale. The researchers developed and evaluated an approach combining large language models (LLMs), semantic embeddings, vector search using FAISS, and different reranking strategies. Experiments were conducted on 30,000 domain names sampled from a collection of nearly 700,000 premium domains, with evaluations involving 22 industry experts and 180 students. The results demonstrated the potential of semantic retrieval to improve domain name recommendations while balancing relevance, diversity, and computational cost.
The research also has clear potential for industrial application. Alicorn, a Montenegro-based software company specializing in solutions for the domain name industry, is already developing AI-powered domain name recommendation technologies, including its Name Sentinel platform. The methods investigated in this study could contribute to further improving such solutions, particularly through more effective semantic search and recommendation of premium domains.
The research represents another example of research and innovation supported by European initiatives and connected with the activities of HPC Montenegro (NCC Montenegro), contributing to the development of AI expertise and stronger links between academia and industry.
Read the scientific paper: IEEE Access – DOI: 10.1109/ACCESS.2026.3740779