Knowledge graph construction method and system for business process optimization

Abstract

The application discloses a knowledge graph construction method and system for business process optimization, and relates to the field of knowledge graph, wherein the method comprises the following steps: receiving and analyzing an input business optimization target, a core entity set, a business constraint rule and a basic operator, generating an initial knowledge graph containing entity nodes, target nodes, constraint nodes and initial relationship connections; connecting the initial knowledge graph to a business process simulation environment, selecting an operation from the basic operator by an intelligent agent, executing a virtual business process, collecting and analyzing interaction logs, extracting an efficient business process path and context features, and converting the efficient business process path and context features into a knowledge subgraph; and fusing and updating the knowledge subgraph in a probabilistic form to the initial knowledge graph. The application solves the technical problems of insufficient dynamic adaptation capability and difficulty in effectively mining efficient execution modes in existing business process optimization, and achieves the technical effects of improving the dynamic adaptation capability and effectively mining efficient process execution modes.

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