Research On Technologies Of Semantic Web Based Automatic Reasoning

The Semantic Web is formally put forward by Berners-Lee, the initiator of WWW, in 2001. The main purpose of the Semantic Web research is to extend the current Web in order to make the information in the network have its semantic understanding, and to be understood and handled by the computer, and to be convenient to the interaction and cooperation between people and computer. So, the importance of research is how to represent the information as the form that computer can understand and handle, that is, the information has its semantic understanding. In order to make computer have the capacity of inference services, first of all, we must make computer understand the knowledge. Because when computer understands the knowledge, it can make inference services. The main purpose of the Semantic Web research is to solve the problem, that is people and computer can understand and handle the knowledge. So, we can develop the inference services base on the semantic Web.This thesis firstly analyzed the framework of the semantic Web and other related knowledge, and then we make the research on the base of logic about ontology. At the end of this thesis, we proposed a reasoning system base on that research. Description logics systems offer a set of typical inference services, such as concept's classification, satisfiability and realization, knowledge base consistency checking. These inference services can find much connotative knowledge and inconsistencies about the knowledge base. The theoretical base of ontology is description logics system, OWL DL and description logics have a good corresponding relation, so we use the OWL DL to build the knowledge base. The advantages of using the OWL DL are as follows: (1) we can find much connotative knowledge and inconsistencies about the knowledge base. (2)we can share and reuse the knowledge better. In order torepair the OWL DL's insufficiency on the inference, we use the SWRL to express the rules, so that we can make reasoning service better. The rule of SWRL is base on the OWL DL, so we can make the knowledge base and the rule connect better. Because the inference engine of the expert system can not directly handle the knowledge of the OWL DL and the rule of SWRL at present, after the ontology is built, we firstly use the tools of providing the description logics reasoning, for example RACER, to reason, then we can find connotative knowledge and inconsistencies about the knowledge base. We secondly use the interface of JessTab provided by Protege to translate from OWL DL format to Jess format, so the inference engine can handle the knowledge base. In addition, we handle the SWRL rule by the use of XSLT. Finally, we transferred the knowledge base and the rule to inference engine to reason.