Medical Documents Search Engine in the Comprehensive Hospital System Using Ontology-Based Semantic Similarity Measurement

• Main Authors: Yousefi, Samaneh, Dami, Sina
• Format: Conference Proceeding
• Language: English
• Subjects: Artificial intelligence; clustering; Hospitals; medical documents; Navigation; Ontologies; ontology; search engine; Search engines; semantic analysis; Semantics; Signal processing
• ISSN: 2640-5768
• DOI: 10.1109/AISP61396.2024.10475239

The structure of comprehensive hospital systems (CHS) shows the way of organizing the links and communications of the pages inside them, its evaluation requires the use of appropriate methods and indicators. The increase in the pages of CHS is so large and complex that navigating through it and finding the desired services or products makes it time-consuming, tiring and even unsuccessful. Considering the expansion of specialized documents in medical records in the CHS and the increase of these documents as possible, access to information in search engines for medical documents in the CHS is becoming more difficult day by day. Therefore, in this research, a new method proposed for medical documents search engine in the CHS using ontology-based semantic similarity to overcome the above problems and provide more concrete and useful results to the treatment staff. In the proposed procedure, first, an ontology matrix was formed for semantic analysis. Then the searched documents were clustered by semantic similarity criteria. Finally, the documents searched by the user were retrieved by calculating the distance of the nearest documents to the cluster center. The experimental outcomes indicate that the proposed procedure surpassed other baseline methods in terms of precision (with 84.08% on average), recall (with 58.56% on average), and f-measure (with 69.06% on average).