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Titlebook: Computational Linguistics and Intelligent Text Processing; 18th International C Alexander Gelbukh Conference proceedings 2018 Springer Natu

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書目名稱Computational Linguistics and Intelligent Text Processing
副標(biāo)題18th International C
編輯Alexander Gelbukh
視頻videohttp://file.papertrans.cn/233/232599/232599.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Linguistics and Intelligent Text Processing; 18th International C Alexander Gelbukh Conference proceedings 2018 Springer Natu
描述.The two-volume set LNCS 10761 + 10762 constitutes revised selected papers from the CICLing 2017 conference which took place in Budapest, Hungary, in April 2017. .The total of 90 papers presented in the two volumes was carefully reviewed and selected from numerous submissions. In addition, the proceedings contain 4 invited papers..The papers are organized in the following topical sections:.Part I: general; morphology and text segmentation; syntax and parsing; word sense disambiguation; reference and coreference resolution; named entity recognition; semantics and text similarity; information extraction; speech recognition; applications to linguistics and the humanities. . .Part II: sentiment analysis; opinion mining; author profiling and authorship attribution; social network analysis; machine translation; text summarization; information retrieval and text classification; practical applications.?.
出版日期Conference proceedings 2018
關(guān)鍵詞artificial intelligence; emotion recognition; internet; learning algorithms; machine translations; natura
版次1
doihttps://doi.org/10.1007/978-3-319-77116-8
isbn_softcover978-3-319-77115-1
isbn_ebook978-3-319-77116-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2018
The information of publication is updating

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,Grundlagen der Str?mungsmechanik,human–annotated affect values. Our framework outperforms the state–of–the–art generic and domain–specific approaches with a precision of over 70% for the emotion detection task on the SemEval 2007 Affect Corpus.
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