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

TL;DR

This paper introduces a scalable, ontology-based information retrieval framework tailored for public transportation data, utilizing semantic indexing and ontology mapping to improve search relevance and system validation.

Contribution

It presents a novel, generic framework for ontology-based retrieval with a focus on scalability and real-world validation in the public transportation domain.

Findings

Framework provides meaningful search results

Semantic indexing improves retrieval efficiency

Validated with real-world data sources

Abstract

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.