Ontology contains a set of concepts and relationships between concepts, and can be applied to information retrieval to process user queries. Challenges in interpreting a query from different ontologies: • It is not possible to determine in advance which ontologies will be relevant for a particular query. • The keyword requested by the user must be translated into ontology-centric terminologies. • Answering a query may require the integration of information from multiple ontologies. Our approach is to keep the ontologies separate. We assume that they use the same description logic, even if they do not use essentially the same vocabulary (i.e. they may use different names for the same concept and/or the same nouns for different concepts). The goal is to create a collaborative system in which ontologies cooperate with each other to answer questions about the information they have. Therefore, in the hope of locating more matches that we need to find, we can use multiple ontologies as background knowledge. There will be a difference in the level of details given by different ontologies on the same domain. This poses additional challenges for selecting the ontology with the precise level of detail. Ontology selection is the process of identifying one or more ontologies that meet certain criteria. These criteria can be linked to the thematic coverage of the ontology. The actual process of checking whether the ontology satisfies certain criteria is fundamentally an ontology evaluation task. In this approach, ontology concepts are compared to a set of query terms that represent the domain. It first tries to determine the ontologies that contain the given keyword. If no match is found, it searches for the term's synonyms and then its hypernyms. The ontology is...... middle of paper ......causes and treatment of milk fever? 0.80 0.95How can we diagnose “hot bronze” disease? 0.75 0.90Which health policies cover treatment of the American plague? 0.25 0.50How can we detect “bad blood” disease in children? 0.45 0.805 ConclusionThis paper presented a method for processing multiple-ontology queries and analyzed case studies on query expansion based on domain-specific ontologies. The use of ontologies for information retrieval, particularly their use in the area of ​​query expansion, is presented. Expanding concept-based queries while retaining the original keywords produces more desirable and useful results. Compound words add complexity to query expansion, but additional search experiments are desirable to study the effects of using an ontology for query expansion. Finally, further research is described for exploiting ontology-based information retrieval in the Cloud..