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Titlebook: Natural Language Processing and Chinese Computing; 12th National CCF Co Fei Liu,Nan Duan,Yu Hong Conference proceedings 2023 The Editor(s)

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發(fā)表于 2025-3-21 17:25:46 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Natural Language Processing and Chinese Computing
副標題12th National CCF Co
編輯Fei Liu,Nan Duan,Yu Hong
視頻videohttp://file.papertrans.cn/662/661812/661812.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Natural Language Processing and Chinese Computing; 12th National CCF Co Fei Liu,Nan Duan,Yu Hong Conference proceedings 2023 The Editor(s)
描述.This three-volume set constitutes the refereed proceedings of the 12th National CCF Conference?on?Natural Language Processing and Chinese Computing, NLPCC 2023, held in Foshan, China,?during?October 12–15, 2023.. The ____ regular papers included in these proceedings were carefully reviewed and?selected from 478 submissions. They were organized in topical sections as follows: dialogue?systems; fundamentals of NLP; information?extraction and?knowledge?graph; machine?learning for NLP; machine?translation and?multilinguality; multimodality and?explainability;?NLP?applications and?text?mining; question?answering; large?language?models; summarization and?generation; student?workshop; and evaluation?workshop..
出版日期Conference proceedings 2023
關(guān)鍵詞Business intelligence; Big data; Intelligent applications; Chinese Computing; Natural Language Processin
版次1
doihttps://doi.org/10.1007/978-3-031-44699-3
isbn_softcover978-3-031-44698-6
isbn_ebook978-3-031-44699-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/n/image/661812.jpg
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https://doi.org/10.1007/978-3-031-44699-3Business intelligence; Big data; Intelligent applications; Chinese Computing; Natural Language Processin
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Conference proceedings 2023edge?graph; machine?learning for NLP; machine?translation and?multilinguality; multimodality and?explainability;?NLP?applications and?text?mining; question?answering; large?language?models; summarization and?generation; student?workshop; and evaluation?workshop..
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Semantic Candidate Retrieval for?Few-Shot Entity Linkingto the mentions are selected by inverted indexing, and then, the semantic ranker is proposed to choose the top appropriate candidate to be linked. The proposed model achieves the accuracy of 53.19% in the shared task 6 of NLPCC-2023.
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