[2603.21139] Ontology-driven personalized information retrieval for XML documents

Computer Science > Information Retrieval arXiv:2603.21139 (cs) [Submitted on 22 Mar 2026] Title:Ontology-driven personalized information retrieval for XML documents Authors:Ounnaci Iddir, Ahmed-ouamer Rachid, Tai Dinh View a PDF of the paper titled Ontology-driven personalized information retrieval for XML documents, by Ounnaci Iddir and 2 other authors View PDF HTML (experimental) Abstract:This paper addresses the challenge of improving information retrieval from semi-structured eXtensible Markup Language (XML) documents. Traditional information retrieval systems (IRS) often overlook user-specific needs and return identical results for the same query, despite differences in users' knowledge, preferences, and objectives. We integrate external semantic resources, namely a domain ontology and user profiles, into the retrieval process. Documents, queries, and user profiles are represented as vectors of weighted concepts. The ontology applies a concept-weighting mechanism that emphasizes highly specific concepts, as lower-level nodes in the hierarchy provide more precise and targeted information. Relevance is assessed using semantic similarity measures that capture conceptual relationships beyond keyword matching, enabling personalized and fine-grained matching among user profiles, queries, and documents. Experimental results show that combining ontologies with user profiles improves retrieval effectiveness, achieving higher precision and recall than keyword-based approaches. ...