Towards Efficient Sport Data Integration through Semantic Annotation

In news genre, the sport domain is one of great interest to audiences on many occasions. The explosion of Internet these days leads to many obstacles for users in searching information due to enormous amount of data collected from multiple media streams. In this case, Semantic Web is believed to bring a solution for information integration. In this paper, we introduce a novel approach for an integration system of sports information using semantic web. Semantic annotation of sport news on the web is a way to bring success to our system. We propose an algorithm to generate semantic annotations of sport news that relies on the ontology. Named entities recognition is improved by integrating the KIM information extraction system with this ontology, which is dedicated for sport domain. The concepts and relations of ontology detected in the text are combined with these entities to capture the semantic. Initial experiments on soccer news demonstrated promising results.