Target identification method and device based on artificial intelligence, electronic equipment and medium

Abstract

The invention relates to the technical field of artificial intelligence, and provides a target identification method and device based on artificial intelligence, electronic equipment and a medium. The method comprises the following steps: acquiring the incidence relation between customers, the label relation between products, and the affiliation relation between customers and preset enterprises; and establishing an initial knowledge graph with the clients as the nodes on the basis of the incidence relation, the label relation and the affiliation relation, wherein the information of the initial knowledge graph is rich, each node in the initial knowledge graph comprises a plurality of attribute features, and therefore the expression ability of the nodes is high; and then performing weight optimization on the initial knowledge graph according to a preset weight optimization strategy to obtain a target knowledge graph. When a graph convolutional neural network is trained based on the target knowledge graph, the training performance of the graph convolutional neural network can be improved, so that the prediction probability of the graph convolutional neural network is improved. The plurality of to-be-identified objects are identified through the trained graph convolutional neural network, so that the target object with relatively high identification accuracy is obtained.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to an artificial intelligence-based target recognition method, device, electronic equipment and medium. Background technique [0002] Discovering high-quality customers and realizing precise and differentiated customer service is an important part of marketing strategy. In the process of realizing the present invention, the inventor found that in the prior art, most of the technologies related to the mining and processing of financial information data, such as the target object identification of high-quality customers, stay at the non-standard and non-quantitative stage, resulting in The target object identification method is single and the identification degree is poor. Although there is a hierarchical analysis model to identify the target object, however, the hierarchical analysis model only involves the single data dimension of the object, resulting in la...

AI Technical Summary

Problems solved by technology

In the process of realizing the present invention, the inventor found that in the prior art, most of the technologies related to the mining and processing of financial information data, such as the target object recognition of high-quality customers, stay in the non-standard and non-quantitative stage, resulting in Disadvantages of single identification method of target object and poor identification degree

Although the target object is identified through the hierarchical analysis model, however, the hierarchical analysis model only involves the single data dimension of the object, resulting in large errors in the identification results of high-quality customers and poor identification accuracy

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