Research On RDF Ontology Query Based Semantic Distance

The unprecedented expansion of the Internet and the dramatical rise in the scale of data increases the difficulty of accessing information, and leads to that the Interent of the time is glutted with a greate deal of meanless information. How to complete quick search and efficient access to information resources in various fields quickly and efficiently has become an important problem to be resolved. In order to solve these problems, Berners-Lee proposed the next generation of the Web development direction, namely Semantic Web, aiming at the more efficient retrieval on imformation that people need by means of making the information on the Web easy to understand. RDF, an abbreviation for Resource Description Framework, is an important part of the semantic Web. As a general metadata model standard, RDF makes the semantic retrieval on the Semantic Web possible, and is has been widely applied in various areas of the semantic Web. With the extensive employment of RDF, the demand to inquiries on the RDF ontology query has become higher.In the RDF ontology query, for one thing, with the increasing of the scope and complexity of the RDF ontology, it is unrealistic to make users to know the structure and contents, and so that too little even empty answers may be returned in response to a user query even if it is explicit, for other thing, different descriptions of the same thing by different persons, ubiquity of multi-word meanings (synonyms) and cases of morphological changes (such as tense, singular and plural, etc) existing in foreign languages are the inevitable problems in RDF ontology query at present. Morever, After the query, users may be confronted with many answers returned, and it will be desirable to have the option of ordering or categorizing the matches automatically in order to deal with information overload, to retrieve results that semantically related to the initial query. For these cases, this paper presents a method based semantic distance. To solve the problem of few or empty answers and synonyms metioned above, we propose a query processing method combining the query relaxation and replacement with kinship words. By using the rules of RDFS on the initial query to relax the query and then choosing the appropriate query to substitute we can get more results. We present the concept of semantic distance to satisfy the demand of returned results that semantically related to the initial query. Through the calculation of the semantic distance, the results semantically close to the initial query will be obtained. On the basis of query procession mentioned above and the semantic distance, we give the query processing algorithm and finally accomplish a simple prototype system. Through the experiments we verify the query processing method. In comparisons with other methods, our method proves to be superior in recall and precision.