Using Ontologies for information retrieval M S Thesis, by R Sandhya, July 2008. Meaningful information retrieval has been an important and interesting research concern in the IR community. Here, the natural emphasis is on retrieving highly relevant information for the given query. Existing keyword based search engines suffer from the problems of retrieving the documents only in the presence of the keyword (along with the statistically computed correlated words), and thus ignoring the documents which do not contain the keyword although semantically relevant and related to the query. On the other hand some of the retrieved documents that contain the query terms may not be relevant. In this context, the user is sometimes overloaded with irrelevant information and sometimes at a loss of data. Being the conceptual models that capture domain knowledge, ontologies can be looked upon for aiding meaningful information retrieval. There have been several efforts towards using the domain knowledge contained in the ontologies for the said purpose. This thesis explores the use of domain specific ontologies in information retrieval. In this thesis, we present a query expansion mechanism which deploys the knowledge of a domain represented in the form of an OWL Ontology to improve relevancy of the retrieved documents. The proposed system fits the query terms in the ontology graph in an appropriate way and exploits the surrounding knowledge to enhance the query. The resulting enhanced query is given to the underlying basic keyword search system. We also propose a way of ranking the results from the basic keyword search system by using the domain ontology. The experiments we have conducted proved a significant increase in the recall and precision when compared to that of keyword search systems. |