Abstract: 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.