Automatic Semantic Retrieval and Visualization Model Based on the Integrated Ontology Library

At present, ontology, by its abundant concept semantic relations、formal share conceptualization model、unified resource description framework, is frequently applied in the expansion of query, semantic indexing of resources、the organization of search results etc. However, by using ontology and ontology-related processing technologies, carrying out an automatic semantic expansion to user query and providing automatic semantic retrieval、conceptual semantic query map of resources etc are still unclear. Therefore, in this paper, we propose an automatic semantic retrieval and visualization model based on the integrated ontology library. This model adopts ontology integration and XML database etc technologies to carry out the ontology integration and storage to the popular ontology libraries, such as WordNet、DBpedia、OpenCyc、SUMO (The Suggested Upper Merged Ontology) etc and forms a normalized integrated ontology library; then under the support of integrated ontology, by XML query language、merging and visualization、query expansion based on conceptual semantic map etc technologies makes an automatic semantic expansion to user query, and provides automatic semantic retrieval、 conceptual semantic query map of resources for users. Experiment results show that our method can filter out a large amount of user query-unrelated information, not only greatly improve the precision of information retrieval system, but also satisfy users’ visual and personalized query requirement.