Research On RDF Ontology Querying Using Query Relaxation Based Semantic Similarity

Semantic Web is the development direction of the next generation of the Web and an extension of the current Internet, whose goal is to make the information on the Web can be understood by machines that makes people retrieve information more efficiently. RDF (Resource Description Framework) is a common metadata model standard, which makes the semantic retrieval in the Semantic Web possible. With more and more extensive application of RDF, RDF ontology in size and complexity is also increasing rapidly and the query on the RDF ontology has become increasingly difficult.In the RDF ontology query, on the one hand, when users have clear intentions but not enough knowledge about the structure and the content of the ontology, there will be an empty or a small number of results returned; on the other hand, after the query relaxation there will be a lot of results returned, there will be a great semantic distant between some of the results and the initial query, then users will want the system to return query results semantically related to the initial query. For both cases, this paper presents a method using query relaxation based semantic similarity.In this paper, we propose a RDF query relaxation method to solve the problem of an empty or a small number of results returned which use the rules of RDFS to get more results. We present the concept of RDF semantic similarity to satisfy the demand of results semantically related to the initial query that wanted to be returned. Through the calculation of the semantic similarity, the results which are semantically related to the initial query will be obtained. On the basis of the above query relaxation strategy and the semantic similarity, we then give a query relaxation algorithm and finally realize a simple prototype system which uses RDF ontology store named Jena SDB supported SPARQL query language. Through the experiments we verify the proposed query relaxation method is feasible. We also make some comparisons with the existing RDF query relaxation methods and prove our method has superiority in response time and recall precision.