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Matches in SemOpenAlex for { <https://semopenalex.org/work/W3117942443> ?p ?o ?g. }

• W3117942443 abstract "In this study, we propose a multi-granularity ordinal classification method to address the problem of emphasis selection. In detail, the word embedding is learned from Embeddings from Language Model (ELMO) to extract feature vector representation. Then, the ordinal classifica-tions are implemented on four different multi-granularities to approximate the continuous em-phasize values. Comparative experiments were conducted to compare the model with baseline in which the problem is transformed to label distribution problem." @default.
• W3117942443 created "2021-01-05" @default.
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• W3117942443 date "2020-01-01" @default.
• W3117942443 modified "2023-09-24" @default.
• W3117942443 title "YNU-HPCC at SemEval-2020 Task 10: Using a Multi-granularity Ordinal Classification of the BiLSTM Model for Emphasis Selection" @default.
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• W3117942443 doi "https://doi.org/10.18653/v1/2020.semeval-1.224" @default.
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