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Record Nr. |
UNISA996511869503316 |
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Titolo |
Computational Linguistics and Intelligent Text Processing . Part II : 19th International Conference, CICLing 2018, Hanoi, Vietnam, March 18-24, 2018, Revised Selected Papers / / Alexander Gelbukh, editor |
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Pubbl/distr/stampa |
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Cham, Switzerland : , : Springer, , [2023] |
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©2023 |
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ISBN |
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Edizione |
[First edition.] |
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Descrizione fisica |
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1 online resource (468 pages) |
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Collana |
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Lecture Notes in Computer Science Series ; ; Volume 13397 |
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Disciplina |
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Soggetti |
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Computational linguistics |
Natural language processing (Computer science) |
Text processing (Computer science) |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Author profiling and authorship attribution, social network analysis -- Information retrieval, information extraction -- Lexical resources -- Best Paper Award, Third Place -- Machine translation -- Morphology, Syntax -- Best Paper Award, Second Place -- Semantics and text similarity -- Sentiment analysis -- Syntax and parsing -- Text categorization and clustering -- Best Paper Award, First Place -- Text generation -- Text mining. |
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Sommario/riassunto |
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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. |
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