Process recommendation model training method, process recommendation method and electronic equipment

Abstract

The invention relates to the technical field of process recommendation, in particular to a process recommendation model training method, a process recommendation method and electronic equipment, and the training method comprises the steps: obtaining sample processing feature sub-graph pairs and target similarity between the sample processing feature sub-graph pairs; the target similarity is determined according to a similarity measurement mode corresponding to the attribute type of each node in the sample processing feature sub-graph pair, and the attribute type comprises a quantitative attribute and a semantic attribute; inputting the sample processing feature sub-graph pair into a preset process recommendation model to obtain a prediction similarity; and based on the difference between the prediction similarity and the target similarity, adjusting parameters of a preset process recommendation model to determine a trained target process recommendation model. The proposed process recommendation model performs recommendation for the process knowledge graph, and the accuracy and recommendation efficiency of the target process recommendation model are improved by converting graph structure data of different node attribute types into a vector form and performing calculation between vectors.

Description

technical field [0001] The invention relates to the technical field of process recommendation, in particular to the training of a process recommendation model, a process recommendation method and electronic equipment. Background technique [0002] With the continuous development and wide application of CAD / CAM systems, a large number of digital 3D CAD models and associated process data / knowledge are continuously generated and stored in the enterprise's data / knowledge base. For enterprises, manufacturing products are not completely independent. Even if they are updated, the structural design and numerical control process of new and old products still have certain similarity and inheritance. Based on this, various process recommendation methods emerge as the times require. [0003] In process recommendation, case-based reasoning (CBR) is an important branch of artificial intelligence. It mainly conducts analogical reasoning based on old instances or experiences, simulating th...

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Problems solved by technology

[0004] In view of this, an embodiment of the present invention provides a process recommendation model training, process recommendation method, and electronic equipment to solve the problem of low efficiency of process recommendation

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