A Generalized Framework for Ontology-Based Information Retrieval Application to a public-transportation system

In this paper we present a generic framework for ontology-based information retrieval. We focus on the recognition of semantic information extracted from data sources and the mapping of this knowledge into ontology. In order to achieve more scalability, we propose an approach for semantic indexing based on entity retrieval model. In addition, we have used ontology of public transportation domain in order to validate these proposals. Finally, we evaluated our system using ontology mapping and real world data sources. Experiments show that our framework can provide meaningful search results.