Research on identification technology of encircled serial tags based on big data and semantic analysis

Abstract

In order to further improve the accuracy of tag recognition, this paper proposes a tag recognition technology based on big data and semantic analysis. Firstly, the big data technology is used to establish the analysis model, identify the behavior of the surrounding tags, and collect and classify the characteristics of the surrounding tags. Based on the complex network, the model of circle recognition is established. Secondly, based on the principle of multi-objective and semantic analysis, the intelligent association rule mining model is constructed to optimize the identification steps of encirclement and collusion in big data. Through the data experimental results, the hidden rules behind the transaction data are revealed, and the transaction track and behavior characteristics of surround bidding and collusion are depicted, so as to effectively reflect the internal institutional root of inducing surround bidding and collusion behavior, which can provide reference for the future The next step of the bidding supervision department is to suit the remedy to the case, establish a comprehensive and effective mechanism for the prevention and control of bidding collusion, and provide strong technical support.