Effective medical resources searching using an ontology‐driven medical information retrieval system: H1N1 case study

As international users increase rapidly, multilingual systems have become a very important service for global users. The purpose of this paper is to design and implement an ontology‐driven medical information retrieval (OMIR) system by building a medical ontology based on the Centers for Disease Control and Prevention's (CDC) medical records.

A traditional cataloging scheme is used as a navigation menu in the CDC system. This traditional cataloging scheme is transformed to a unique medical ontology for global users in the OMIR system. An experimental study was conducted on both an ontology‐driven medical information system (OMIR) and the CDC system.

The medical ontology can be used to filter out unsuitable resources based on semantic relationships. In addition, the recommended resources can be categorized and provide the patron with different languages to access resources. The OMIR system provides better relevancy and shorter search times compared with alternative systems.

The OMIR system is currently implemented for medical resources from the CDC. The developed method may also be applied to other domain areas.

This paper represents a practical method of building a multilingual medical information retrieval system and explains the functional use of ontological knowledge. This study provides insights into medical information seeking performance on the medical database systems.