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Titlebook: Computational Linguistics and Intelligent Text Processing; 19th International C Alexander Gelbukh Conference proceedings 2023 Springer Natu

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書目名稱Computational Linguistics and Intelligent Text Processing
副標(biāo)題19th International C
編輯Alexander Gelbukh
視頻videohttp://file.papertrans.cn/233/232595/232595.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Linguistics and Intelligent Text Processing; 19th International C Alexander Gelbukh Conference proceedings 2023 Springer Natu
描述The two-volume set LNCS 13396 and 13397 constitutes revised selected papers from the CICLing 2018 conference which took place in Hanoi, Vietnam, in March 2018..The total of 68 papers presented in the two volumes was carefully reviewed and selected from 181 submissions. The focus of the conference was on following topics such as computational linguistics and intelligent text and speech processing and others. ..The papers are organized in the following topical?sections: General, Author profiling and authorship attribution, social network analysis, Information retrieval, information extraction, Lexical resources, Machine translation, Morphology, syntax, Semantics and text similarity, Sentiment analysis, Syntax and parsing, Text categorization and clustering, Text generation, and? Text mining. .
出版日期Conference proceedings 2023
關(guān)鍵詞artificial intelligence; computational linguistics; computer science; computer systems; correlation anal
版次1
doihttps://doi.org/10.1007/978-3-031-23793-5
isbn_softcover978-3-031-23792-8
isbn_ebook978-3-031-23793-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2023
The information of publication is updating

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Argumentation in?Text: Discourse Structure Mattersicative discourse tree (CDT) is used. It consists of a discourse tree (DT) with additional labels on edges, which stand for verbs. These verbs represent communicative actions. Discourse trees are based on rhetoric relations, extracted from a text according to Rhetoric Structure Theory. The problem i
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A Deep Learning Approach for?Multimodal Deception Detectionper, we propose a simple yet tough to beat multimodal neural model for deception detection. By combining features from different modalities such as video, audio, and text along with Micro-Expression features, we show that detecting deception in real life videos can be more accurate. Experimental res
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Analyzing Stylistic Variation Across Different Political Regimesulturally: communism and democracy in Romania. We aim to analyze the stylistic variation between texts written during these two periods, and determine at what levels the variation is more apparent (if any): at the stylistic level, at the topic level etc. We take a look at the stylistic profile of th
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