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- W4327773765 abstract "In view of the limited utilization of fault knowledge value in the power field, this paper explores the automatic term extraction for knowledge graph in the power field to solve the cold start problem of lack of large-scale annotated corpus. We design a TTL model consisting of text representation, feature extraction, and sequence labeling, which realizes the knowledge transfer from the annotated corpora in the source domain to the target domain in the power grid domain. With Transformer as the skeleton, the model is used to adequately model semantic associations between words. The experiments on a real dataset show the effectiveness of the proposed model." @default.
- W4327773765 created "2023-03-19" @default.
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- W4327773765 date "2022-12-09" @default.
- W4327773765 modified "2023-10-18" @default.
- W4327773765 title "A Transfer Learning based Model for Knowledge Graph in Power Grid" @default.
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- W4327773765 doi "https://doi.org/10.1109/iaecst57965.2022.10061887" @default.
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