OGC Geographic Information Service Deductive Semantic Reasoning Method Research Based On Description Vocabularies Reduction

With the development of geographic information sharing and interoperability, a growingnumber of geographic information services is formed and released through network. However, theability of geographic information services in effectively organization and expression of geospatialknowledge is relatively weak, and lacking of semantic description of service information results inthe defects in representation and retrieval of existing data. What described by one geographicinformation service is more often than not an isolated geographical semantics. There are alwaysproblems of semantic differences, such as the focus in varied areas or diverseproblem-solving-system is different, resulting from the semantic inconsistency among geographicinformation classification systems. When systems access, retrieve and integrate application of thesegeographic information services, users are difficult to obtain, or acquire insufficiently thegeographic information services they really need due to the semantic differences.This paper considers OGC geographic information services as the studied object, andintroduces the rough set theory related methods. Through researching in semantic description,knowledge reduction and semantic reasoning, we effectively solute the deficiencies in knowledgerepresentation and semantics search reasoning of OGC geographic information services.Dissertation research is conducted as follows:(1) By introducing geographic ontology, classifying in accordance with the fundamentalgeographic information elements, extracting the description vocabulary of OGC geographicinformation services, and building OGC geographic information services semantic ontology andexamples description database, a complete integration description geographic ontology model ofspatial and attribute is formed.(2) Establish the integration description vocabulary reduction model of attribute and spatialrules for OGC geographic information services with ontology model and rough set theory. Based onthis model, we achieve the knowledge reduction of the instance description database of the OGCgeographic information services and get the best instance description database.(3) With the application of the OGC geographic information services ontology library and thebest instance description database and the geographic ontology query expansion technique, wedesign and develop a semantic reasoning prototype system with high recall ratio and high precisionratio oriented for the OGC geographic information services. This system can help us achieve semantic retrieval, semantic reasoning and semantic similarity estimate based on matching results,taking the spatial relationship into account in OGC geographic information services.(4)Based on the semantic reasoning prototype system for the OGC geographic informationservices, we achieve semantic retrieval and reasoning of the object of the OGC geographicinformation services by searching for examples. The feasibility, validity and accuracy of this systemis verified by the recall ratio, precision ratio and searching time of the system.This paper researches on OGC geographic information service deductive semantic reasoning, andverifies experimental methods through the various validation experiments. That shows: the methodthis paper put forward improves the recall ratio and and precision ratio of semantic reasoningsystem which is up to85%. Meanwhile, ensuring high recall ratio and precision ratio, systemretrieval time is also relatively lower.It indicates that the OGC geographic information servicessemantic reasoning methods in aspects of the query success rate, efficiency and other performanceof system are greatly improved.