The current human society is entering an era of artificial intelligence that integrates data-driven and knowledge-driven approaches. Knowledge graph, a technique that has gained significant attention in recent years within the field of artificial intelligence, utilizes a graphical structure to represent knowledge and model the relationships between various entities in the world. The essence of constructing a knowledge graph lies in efficiently and accurately uncovering the associations among different entities. Data mining, which involves extracting potentially valuable information and knowledge from large datasets, provides technical support for building knowledge graphs. This paper primarily discusses the application of data mining techniques in constructing knowledge graphs, proposes implementation pathways for these techniques at various stages of knowledge graph construction, and offers support for creating high-quality knowledge graphs.
With the development of cloud-native technology, service mesh realizes reliable request delivery in the complex service topology of cloud-native applications. Aiming at the problems in the role-based access control model in the Istio service mesh, this paper adds a service mesh authorization control based on user behavior credibility. The purpose is to continuously monitor user behavior, ensure user identity is credible, regulate user behavior, and prevent others from malicious attacks and impersonating identity to steal information within the scope of user authority.
With the expansion of smart devices in 5G, Internet of Things, mobile Internet and other technical scenarios, the number of devices on the edge of the network has increased dramatically. In the edge computing scene, there are a large number of heterogeneous devices, each of which has its own unique characteristics and attributes. For the edge scene, due to the increasing requirements of massive data on the timeliness, security and network dependence of computing facilities, the current cloud platform with Kubernetes as the core is not fully applicable. Therefore, many open source frameworks came into being, and KubeEdge [1] is one of the representatives. Aiming at KubeEdge, this paper proposes a cloud-edge collaboration scheme, which deploys the surface defect recognition algorithm based on YOLOv5 network to cloud edge devices to realize surface defect recognition and node autonomy in edge scenes, and provides a solution for cloud edge collaboration scenes.
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