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Titlebook: Chinese ComputationalLinguistics; 20th China National Sheng Li,Maosong Sun,Gaoqi Rao Conference proceedings 2021 Springer Nature Switzerla

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书目名称Chinese ComputationalLinguistics
副标题20th China National
编辑Sheng Li,Maosong Sun,Gaoqi Rao
视频videohttp://file.papertrans.cn/226/225764/225764.mp4
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Chinese ComputationalLinguistics; 20th China National  Sheng Li,Maosong Sun,Gaoqi Rao Conference proceedings 2021 Springer Nature Switzerla
描述This book constitutes the proceedings of the 20th China National Conference on Computational Linguistics, CCL 2021, held in Hohhot, China, in August 2021..The 31 full presented in this volume were carefully reviewed and selected from 90 submissions...The conference papers covers the following topics such as Machine Translation and Multilingual Information Processing, Minority Language Information Processing, Social Computing and Sentiment Analysis, Text Generation and Summarization, Information Retrieval, Dialogue and Question Answering, Linguistics and Cognitive Science, Language Resource and Evaluation, Knowledge Graph and Information Extraction, and NLP Applications. .
出版日期Conference proceedings 2021
关键词computational linguistics; computer systems; computer vision; databases; education; image processing; info
版次1
doihttps://doi.org/10.1007/978-3-030-84186-7
isbn_softcover978-3-030-84185-0
isbn_ebook978-3-030-84186-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

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Chinese ComputationalLinguistics978-3-030-84186-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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https://doi.org/10.1007/978-3-030-84186-7computational linguistics; computer systems; computer vision; databases; education; image processing; info
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,On Yen’s Path Logic for Petri Nets,se of the beam size often suffers from plenty of short translations, resulting in dramatical decrease in translation quality. In this paper, we handle the length bias problem through a perspective of causal inference. Specifically, we regard the model generated translation score . as a degraded true
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Kenneth L. McMillan,Lenore D. Zuckent learning affect the performance of the model. The reward for generating translation is determined by the scalability and iteration of the sampling strategy, so it is difficult for the model to achieve bias-variance trade-off. Therefore, according to the poor ability of the model to analyze the s
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Lecture Notes in Computer Sciencehe emotion cause at the clause level. However, in many scenarios, only extracting the cause clause is ambiguous. To ease the problem, in this paper, we introduce multi-level emotion cause analysis, which focuses on identifying emotion cause clause (ECC) and emotion cause keywords (ECK) simultaneousl
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