Semantic Search Based Qaal System Using Qgt Graph Matching with Semantic Similarity

The second phase of QA system is the query processing model in which the given query is matched with the terms used in ontology by using semantic pattern matching type. In question classification model, the given question is converted into query form and the answer is tested by using Q2Q algorithm. But, semantic pattern type of matching is not processed in it. In this chapter, pattern matching techniques are proposed and analyzed in given query in RDF graph based pattern matching technique based on similarity measurement analysis based on concepts, relations and graphs for matching the resultant query terms with the terms in knowledge base. The terms are framed as SPARQL queries in this thesis. In SPARQL query, four categories of query interfaces are used for retrieving answers from ontology. this issue and it is categorized as keyword-based, form-based, view-based and natural language-based systems. Among these, keyword-based system interface is mostly used. It is a challenging one to combine keyword-based interfaces with semantic