| Title | Entity Extraction Algorithm of Hybrid Network based on Attention Mechanism in Smart City |
|---|---|
| ID_Doc | 41469 |
| Authors | Yan, ZF; Yang, Y; Gao, ZP; Zhao, LJ; Wang, Z; Cui, DD |
| Title | Entity Extraction Algorithm of Hybrid Network based on Attention Mechanism in Smart City |
| Year | 2022 |
| Published | |
| Abstract | With the continuous development of information and communication network technology, the number of devices in the network and the running data are increasing geometrically, which brings certain challenges to network configuration, operation and maintenance and management. At present, with the vigorous development of artificial intelligence technology, the concept of intelligent operation and maintenance came into being. The construction of hybrid network knowledge graph is an important part of intelligent operation and maintenance, and hybrid network entity extraction is a key step in its construction. Therefore, in order to effectively identify hybrid network entities, this paper proposes hybrid network entity extraction algorithm based on attention mechanism. Using the multi-head attention mechanism combined with the bidirectional long and short-term memory network and CRF, the accuracy of the neural network model is further improved. In order to verify the effectiveness of the method, we compare the improved algorithm in this paper with the existing classical algorithms and literature algorithms. The experiments show that the algorithm in this paper has certain effectiveness and superiority. |
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