基于本体推理和数据挖掘的良好农业规范专家系统

针对良好农业规范(good agricultural practices，GAP)标准内容复杂，不易被农业生产者准确使用的问题，将本体推理和数据挖掘技术相结合，构建了良好农业规范专家系统，实现标准知识查询和GAP控制点推荐等功能，更好的帮助生产者理解和使用GAP。系统构建过程中，采用本体知识表示方法构建GAP标准知识库，通过解析“良好农业规范生产和认证信息服务平台”的GAP电子检查表记录，对挖掘过程中涉及的关联规则算法进行分析和改进，挖掘分析了用户对控制点使用的偏好。设计了控制点评价模型，实现了GAP控制点的择优推荐。系统基于MVC模式，设计为3层体系架构。通过测试应用，用户能够准确和容易的使用GAP标准。

Expert System for GAP Based on Ontology and Data Mining

In order to resolve the problem that GAP is so complex for farmers to use it accurately, this paper presented the combination of ontology and data mining that could be used to build expert system for GAP in farming products field. This expert system provided the function of GAP control point recommendation which could help farms better understand and use GAP. In the construction of the system, the researchers built the knowledge base of GAP standard with ontology and the preference rule base by analyzing the records of GAP control points from the“GAP production and certification services platform”with the improved association rule algorithm. To recommend the best control points for farms, the researchers designed a control point evaluation model which could allow people to take account of the experience of experts, as well as factors such as preference. The expert system was designed into three layers according to the MVC pattern. The application results showed that the implementation of the expert system could allow users to use GAP accurately and easily.