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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
DOI 10.1109/ICAIT56197.2022.9862644
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.
Author Keywords intelligent operation and maintenance; hybrid network knowledge graph; entity extraction; multi-head attention mechanism
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Conference Proceedings Citation Index - Science (CPCI-S)
EID WOS:000860757600064
WoS Category Computer Science, Information Systems; Telecommunications
Research Area Computer Science; Telecommunications
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