Smart Sociolinguistic Intelligent Analysis Framework Based on Feature Extraction and Matching of Structural Data

Smart sociolinguistic intelligent analysis framework based on feature extraction and the matching of structural data is designed in this paper. Since data mining has added annotations to the features of the search data, when searching and searching data, it is faster and more accurate than traditional statistical analysis methods. This paper uses the SUSAN features, the method is simple, the anti-noise ability is strong, and the processing speed is fast. The matching similarity measurement should also consider the feature point direction information to integrate the structure features. For target matching, the side direction information can be directly represented by the feature vector formed by the two-directional cross template response, and the framework is then completed. The model is validated through the public data and the collected data from the Internet.