Adaptive Recommendation Method for Food Sampling Inspection Based on Data Mining

This research uses data mining technology to propose a food sampling inspection model based on an adaptive algorithm, customize the way of perceiving food unit adaptation, formulate a targeted and reasonable sampling plan, and use the Internet to improve the level of sampling . First, design the overall framework of the adaptive model, including sampling capabilities and cognitive capabilities; secondly, current capabilities of each unit to facilitate the higher identification characteristics of the Internet established by the adaptive model, and use it as a self-recognition Adapt to the basis of the sampling inspection recommendation plan; finally, compare and analyze the improvement of the food sampling inspection based on the adaptive algorithm from the two aspects.