Matches in SemOpenAlex for { <https://semopenalex.org/work/W4323866504> ?p ?o ?g. }
Showing items 1 to 82 of
82
with 100 items per page.
- W4323866504 endingPage "8850" @default.
- W4323866504 startingPage "8841" @default.
- W4323866504 abstract "The fault diagnosis of vessel power equipment is established by the manual work with low efficiency. The knowledge graph(KG) usually is applied to extract the experience and operation logic of controllers into knowledge, which can enrich the means of fault judgment and recovery decision. As an important part of KG building, the performance of named entity recognition (NER) is critical to the following tasks. Due to the challenges of information insufficiency and polysemous words in the entities of vessel power equipment fault, this study adopts the fusion model of Bidirectional Encoder Representations from Transformers (BERT), revised Convolutional neural network (CNN), bidirectional long short-term memory (BiLSTM), and conditional random field (CRF). Firstly, the adjusted BERT and revised CNN are respectively adopted to acquire the multiple embeddings including semantic information and contextual glyph features. Secondly, the local context features are effectively extracted by adopting the channel-wised fusion structures. Finally, BiLSTM and CRF are respectively adopted to obtain the semantic information of the long sequences and the prediction sequence labels. The experimental results show that the performance of NER by the proposed model outperforms other mainstream models. Furthermore, this work provides the foundation of the tasks of intelligent diagnosis and NER in other fields." @default.
- W4323866504 created "2023-03-11" @default.
- W4323866504 creator A5038281085 @default.
- W4323866504 creator A5043427498 @default.
- W4323866504 creator A5062430620 @default.
- W4323866504 date "2023-06-01" @default.
- W4323866504 modified "2023-10-16" @default.
- W4323866504 title "The named entity recognition of vessel power equipment fault using the multi-details embedding model" @default.
- W4323866504 cites W2967649271 @default.
- W4323866504 cites W2973965787 @default.
- W4323866504 cites W3037333170 @default.
- W4323866504 cites W3045156229 @default.
- W4323866504 cites W3117492161 @default.
- W4323866504 cites W3123194504 @default.
- W4323866504 cites W3157876196 @default.
- W4323866504 cites W3213591530 @default.
- W4323866504 cites W4211043794 @default.
- W4323866504 cites W4213155040 @default.
- W4323866504 doi "https://doi.org/10.3233/jifs-223200" @default.
- W4323866504 hasPublicationYear "2023" @default.
- W4323866504 type Work @default.
- W4323866504 citedByCount "0" @default.
- W4323866504 crossrefType "journal-article" @default.
- W4323866504 hasAuthorship W4323866504A5038281085 @default.
- W4323866504 hasAuthorship W4323866504A5043427498 @default.
- W4323866504 hasAuthorship W4323866504A5062430620 @default.
- W4323866504 hasConcept C111919701 @default.
- W4323866504 hasConcept C118505674 @default.
- W4323866504 hasConcept C119857082 @default.
- W4323866504 hasConcept C121332964 @default.
- W4323866504 hasConcept C132525143 @default.
- W4323866504 hasConcept C142816647 @default.
- W4323866504 hasConcept C152565575 @default.
- W4323866504 hasConcept C154945302 @default.
- W4323866504 hasConcept C165801399 @default.
- W4323866504 hasConcept C204321447 @default.
- W4323866504 hasConcept C2775953691 @default.
- W4323866504 hasConcept C36464697 @default.
- W4323866504 hasConcept C41008148 @default.
- W4323866504 hasConcept C41608201 @default.
- W4323866504 hasConcept C62520636 @default.
- W4323866504 hasConcept C66322947 @default.
- W4323866504 hasConcept C80444323 @default.
- W4323866504 hasConcept C81363708 @default.
- W4323866504 hasConceptScore W4323866504C111919701 @default.
- W4323866504 hasConceptScore W4323866504C118505674 @default.
- W4323866504 hasConceptScore W4323866504C119857082 @default.
- W4323866504 hasConceptScore W4323866504C121332964 @default.
- W4323866504 hasConceptScore W4323866504C132525143 @default.
- W4323866504 hasConceptScore W4323866504C142816647 @default.
- W4323866504 hasConceptScore W4323866504C152565575 @default.
- W4323866504 hasConceptScore W4323866504C154945302 @default.
- W4323866504 hasConceptScore W4323866504C165801399 @default.
- W4323866504 hasConceptScore W4323866504C204321447 @default.
- W4323866504 hasConceptScore W4323866504C2775953691 @default.
- W4323866504 hasConceptScore W4323866504C36464697 @default.
- W4323866504 hasConceptScore W4323866504C41008148 @default.
- W4323866504 hasConceptScore W4323866504C41608201 @default.
- W4323866504 hasConceptScore W4323866504C62520636 @default.
- W4323866504 hasConceptScore W4323866504C66322947 @default.
- W4323866504 hasConceptScore W4323866504C80444323 @default.
- W4323866504 hasConceptScore W4323866504C81363708 @default.
- W4323866504 hasIssue "6" @default.
- W4323866504 hasLocation W43238665041 @default.
- W4323866504 hasOpenAccess W4323866504 @default.
- W4323866504 hasPrimaryLocation W43238665041 @default.
- W4323866504 hasRelatedWork W2096567921 @default.
- W4323866504 hasRelatedWork W2135348717 @default.
- W4323866504 hasRelatedWork W2151982765 @default.
- W4323866504 hasRelatedWork W2395488739 @default.
- W4323866504 hasRelatedWork W2548958971 @default.
- W4323866504 hasRelatedWork W2577088515 @default.
- W4323866504 hasRelatedWork W3048861483 @default.
- W4323866504 hasRelatedWork W3089044186 @default.
- W4323866504 hasRelatedWork W3095092693 @default.
- W4323866504 hasRelatedWork W4230401652 @default.
- W4323866504 hasVolume "44" @default.
- W4323866504 isParatext "false" @default.
- W4323866504 isRetracted "false" @default.
- W4323866504 workType "article" @default.