Agriculture Knowledge Services-Ant Colony Algorithm And Semantic Reasoning

Along with the development of the information technology and the improvement of the social informationization, information acquisition has already been an important part of the human life, and the information service has developed into the knowledge service which is more efficient and accurate. How to prove the standard of the knowledge service is the hotspot in this research field. People began to try Ontology, Semantic Web, and the biological reasoning algorithm based on the mathematical simulation for the knowledge organization and knowledge management, and try to develop highly efficient knowledge service system. This study is exploring to build a semantic reasoning model based on the ant colony algorithm for the Agri-knowledge service system. The study also support the Agri-knowledge search engine with the basement method, thus to prove the standard of the Agri-knowledge organization, management and service.Firstly,this paper introduced the Web Service and Grid Computing which the study involved, and designed the frame of the Agri-knowledge service system based on the semantic web, introduced and analyzed the system which contains upper service module, semantic inductive module, knowledge data administration module, knowledge data acquisition module and web-service module. The study supplied the knowledge service system development with the theory frame.Secondly, introduced the Ontology, Semantic Reasoning, Topic Semantic Comparability(TSC) and Ant Colony Algorithm(ACA) which the Reasoning model involved in the system, and supplied the theory for the parser in the reasoning model.Thirdly, designed the semantic reasoning model based on the TSC and ACA, the model can parse and execute the query, and reason the SWRL in the knowledge base to get the result. The parser algorithm is based on the TSC and ACA, the algorithm can retrieve the knowledge base for the proper rules according to the input, thus support the semantic reasoning model with the retrieval algorithm.Lastly, offered a development process for the semantic reasoning model, and realized the mandarin fish disease diagnose system using the development process, the successes of the system development showed the design is effective.