Research on Entity Update Technology for Fault Diagnosis Knowledge Graph of Cloud Data Center

Abstract

The Fault Diagnosis Knowledge Graph (FDKG) of Cloud Data Center (CDC), in a broad sense, is the knowledge Digital Twin of the fault phenomenon, reasoning, and maintenance process of Cloud Data Center in the physical world. The key to the Digital Twin is to establish the information interface between the physical space and the virtual space, and the key to the construction of the fault diagnosis KG is also here. FDKG of The State Grid Cloud Data Center needs to integrate multi-source knowledge to establish an information interface with the CDCs of subsidiaries in each province. However, in the process of updating the FDKG, the entity name attribute represented by long sentences reduces the accuracy of entity alignment, and it is difficult to efficiently integrate knowledge into the FDKG without increasing knowledge redundancy. This paper proposes an entity alignment method based on the fusion of attribute and relationship similarity, which will use the clearly defined relationship information in the FDKG to effectively improve the accuracy of entity alignment. The knowledge update tool developed based on this, effectively improves the entity alignment accuracy of the FDKG, and improves the information interface connection efficiency of the FDKG of the CDC.