Study On The Semantic Retrieval Of Ontology Of Forestry Pests And Diseases

With the continuous expansion of forestry information resources,the resulting problems of information retrieval continue to emerge,such as the lower level of intelligence of information retrieval,the one-sideness of the user query results and so on.Under the framework of the semantic web,combining ontology knowledge with existing information retrieval technology has become a new solution to the problems mentioned above.It is very important to construct the domain ontology semantic web framework by using the core concept of a distinctive field of forestry,which is of great significance to improve the accuracy and comprehensiveness of information retrieval in the field of forestry.At present,there are few researches on semantic retrieval of forestry field ontology,but many research methodologies of ontological semantics in related fields have a certain reference significance to the research direction of this paper.Built on the data of forest pests and diseases,this paper constructs the domain ontology knowledge base by using the ontology and semantic pre-processing knowledge,and enables the machine to do semantic analysis and inference of the data in the domain.And then,the query results will be better meet the user's core needs through the semantic extension based on the constructed ontology library of the query terms.The core content of this paper is as follows:Through the research on the theory of domain ontology construction,based on the data of forest pests and diseases,the ontology knowledge base based on forestry pests and diseases will be constructed with the use of ontology construction seven-step method,and experts in this field are invited to provide theoretical guidance and assistance in order to improve the constructed knowledge base.After that,it will introduce the edge weight relation and semantic relevance factor,and combine them with the existing semantic similarity influence factor of ontology to propose an improved semantic similarity algorithm of ontology concept that has been proved to be economical and effective through experiments.At the same time,according to the optimized algorithm,an efficient semantic query expansion model is proposed,which offers an essential foundation for the semantic retrieval model proposed below.A semantic retrieval system model based on the ontology of forest pest and disease is realized by requirement analysis and the detailed design of the system frame and various functional modules in combination with the constructed ontology library and semantic query expansion model of forestry pests and diseases.Experiments and result analysis are performed to verify the validity and feasibility of this paper.It is demonstrated that the progress of the model compared to the traditional one improves the retrieval precision and recall rate to a certain extent.Finally,the paper summarizes the innovation points and existing problems in the research,and puts forward constructive suggestions for the solution of the problems.