Research on false data automatic identification of live broadcast platform with goods based on double low rank constraint

In order to solve the problem of low accuracy of false data feature extraction and false data identification existing in the traditional automatic identification method of false data of live broadcasting platform, this paper proposes an automatic identification method of false data of live broadcasting platform based on double low rank constraint. In order to identify the false data in the data environment of live broadcasting platform, firstly, the characteristics of the false data in the platform are extracted to distinguish the false data from the real data. According to the calculation of the state space feature subset of the false data in the fuzzy clustering, the mapping function of the false data in the feature space is obtained. The results of false data feature extraction are obtained by least square calculation. The false data identification control function is constructed. According to the identification control function, the data separated from the bad data is represented by the double low rank constraint method. In order to fully extract the false data features of live broadcast platform, the state space feature subset of false data is calculated according to fuzzy clustering. Under the constraint of double low rank, the iterative results are solved to get the false data identification of live broadcast platform. Experimental results show that, compared with traditional recognition methods, this method has higher accuracy of false data feature extraction and recognition.