Semantic Retrieval Research Based On Ontology

As the global network, information technology development, information retrieval technology in dealing with the explosive growth of online information resources is very important. However, traditional information retrieval techniques is mainly based on string matching keyword search technology, the ability to support poor semantic matching, information retrieval recall rate and precision rate far from satisfactory. To this end, Tim Berners-Lee in 2000 proposed the concept of the next generation of World Wide Web, Semantic Web, seeks to provide the World Wide Web resources on the unique identifier, and resources to build machines capable of handling between the various types of semantic links. Semantic Web is an extension of the contemporary World Wide Web can be a clear and formal way to represent information resources. Semantic Web presentation and development of semantic retrieval achieve opened up a new way of thinking.To achieve a better Semantic Web vision, Web of Knowledge Representation is the most fundamental and most important issue. Ontology (Ontology) as a shared conceptual model of the formal specification, can be one area of the real world into a set of abstract concepts and the relationship between the concepts, providing a field of universal, shared knowledge representation, and this knowledge can be the computer to understand. Ontology as a Semantic Web vision to achieve a bridge, which one end is the syntax to express the real world, the other side of this is the expression of abstract models. Through a variety of information resources to the ontology mapping and semantic reasoning layer processing, to fully tap the resources of the association between the implied and thus fundamentally solve the retrieval of the resource objects of the issue of the lack of semantic information to meet the user resource object semantic retrieval needs.This article first introduced the Semantic Web and ontology of knowledge and their applications, and information retrieval theory is studied. This detailed comparison of the traditional information retrieval and semantic retrieval ontology-based differences, and provide examples of functional comparison. Information storage is a prerequisite for information retrieval, for which we then studied the ontology storage, and a storage method has been improved. Finally, we propose an ontology-based semantic retrieval system model, the key feature of the model blocks were analyzed, and key technologies were studied. According to ontology construction method, we constructed a body of expert information, and semantic search engine was studied.In order to verify the feasibility of semantic retrieval theory, we constructed a computer course information area of ontology, and developed a prototype of the semantic retrieval system, based on the theoretical of the analysis. The system achieved a relatively simple semantic search, provided the function of semantic reasoning, which are difficult to achieve by traditional search methods, and fully reflects the Semantic Web search technology as opposed to general search technology superiority.