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Titlebook: Natural Language Processing and Chinese Computing; 10th CCF Internation Lu Wang,Yansong Feng,Ruifang He Conference proceedings 2021 Springe

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書(shū)目名稱(chēng)Natural Language Processing and Chinese Computing
副標(biāo)題10th CCF Internation
編輯Lu Wang,Yansong Feng,Ruifang He
視頻videohttp://file.papertrans.cn/662/661803/661803.mp4
叢書(shū)名稱(chēng)Lecture Notes in Computer Science
圖書(shū)封面Titlebook: Natural Language Processing and Chinese Computing; 10th CCF Internation Lu Wang,Yansong Feng,Ruifang He Conference proceedings 2021 Springe
描述This two-volume set of LNAI 13028 and LNAI 13029 constitutes the refereed proceedings of the 10th CCF Conference on Natural Language Processing and Chinese Computing, NLPCC 2021, held in Qingdao, China, in October 2021..The 66 full papers, 23 poster papers, and 27 workshop papers presented were carefully reviewed and selected from 446 submissions. They are organized in the following areas: Fundamentals of NLP; Machine Translation and Multilinguality; Machine Learning for NLP; Information Extraction and Knowledge Graph; Summarization and Generation; Question Answering; Dialogue Systems; Social Media and Sentiment Analysis; NLP Applications and Text Mining; and Multimodality and Explainability..
出版日期Conference proceedings 2021
關(guān)鍵詞artificial intelligence; computational linguistics; data mining; databases; Human-Computer Interaction (
版次1
doihttps://doi.org/10.1007/978-3-030-88483-3
isbn_softcover978-3-030-88482-6
isbn_ebook978-3-030-88483-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2021
The information of publication is updating

書(shū)目名稱(chēng)Natural Language Processing and Chinese Computing影響因子(影響力)




書(shū)目名稱(chēng)Natural Language Processing and Chinese Computing影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Natural Language Processing and Chinese Computing網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Natural Language Processing and Chinese Computing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Natural Language Processing and Chinese Computing被引頻次




書(shū)目名稱(chēng)Natural Language Processing and Chinese Computing被引頻次學(xué)科排名




書(shū)目名稱(chēng)Natural Language Processing and Chinese Computing年度引用




書(shū)目名稱(chēng)Natural Language Processing and Chinese Computing年度引用學(xué)科排名




書(shū)目名稱(chēng)Natural Language Processing and Chinese Computing讀者反饋




書(shū)目名稱(chēng)Natural Language Processing and Chinese Computing讀者反饋學(xué)科排名




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Searching Effective Transformer for Seq2Seq Keyphrase Generational Language Processing (NLP). Recently, the Transformer structure with fully-connected self-attention blocks has been widely used in many NLP tasks due to its advantage of parallelism and global context modeling. However, in KG tasks, Transformer-based models can hardly beat the recurrent-based mode
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