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Recent advances in NLP = the case of...

Abd Elaziz, Mohamed.

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Recent advances in NLP = the case of Arabic Language /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Recent advances in NLP/ edited by Mohamed Abd Elaziz ... [et al.].
其他題名:	the case of Arabic Language /
其他作者:	Abd Elaziz, Mohamed.
出版者:	Cham :Springer International Publishing : : 2020.,
面頁冊數:	xiv, 209 p. :ill., digital ;24 cm.
內容註:	Text summarization: A brief review -- Single Arabic Document Summarization Using Natural Language Processing Technique -- Proposed Natural Language Processing Preprocessing Procedures for Enhancing Arabic Text Summarization -- Effects of Stemming on Feature Extraction and Selection for Arabic Documents Classification -- Improving Arabic Lemmatization through a lemmas database and a machine-learning technique -- The role of transliteration in the process of Arabizi translation/sentiment analysis -- Sentiment analysis in healthcare: A brief review -- Aspect-Based Sentiment Analysis for Arabic Government Reviews -- Prediction of the Engagement Rate on Algerian Dialect Facebook Pages -- Predicting Quranic Audio Clips Reciters Using Classical Machine Learning Algorithms: A Comparative Study.
Contained By:	Springer eBooks
標題:	Natural language processing (Computer science) -
電子資源:	https://doi.org/10.1007/978-3-030-34614-0
ISBN:	9783030346140

Recent advances in NLP = the case of Arabic Language /
Recent advances in NLPthe case of Arabic Language /[electronic resource] :edited by Mohamed Abd Elaziz ... [et al.]. - Cham :Springer International Publishing :2020. - xiv, 209 p. :ill., digital ;24 cm. - Studies in computational intelligence,v.8741860-949X ;. - Studies in computational intelligence ;v.874..

Text summarization: A brief review -- Single Arabic Document Summarization Using Natural Language Processing Technique -- Proposed Natural Language Processing Preprocessing Procedures for Enhancing Arabic Text Summarization -- Effects of Stemming on Feature Extraction and Selection for Arabic Documents Classification -- Improving Arabic Lemmatization through a lemmas database and a machine-learning technique -- The role of transliteration in the process of Arabizi translation/sentiment analysis -- Sentiment analysis in healthcare: A brief review -- Aspect-Based Sentiment Analysis for Arabic Government Reviews -- Prediction of the Engagement Rate on Algerian Dialect Facebook Pages -- Predicting Quranic Audio Clips Reciters Using Classical Machine Learning Algorithms: A Comparative Study.

In light of the rapid rise of new trends and applications in various natural language processing tasks, this book presents high-quality research in the field. Each chapter addresses a common challenge in a theoretical or applied aspect of intelligent natural language processing related to Arabic language. Many challenges encountered during the development of the solutions can be resolved by incorporating language technology and artificial intelligence. The topics covered include machine translation; speech recognition; morphological, syntactic, and semantic processing; information retrieval; text classification; text summarization; sentiment analysis; ontology construction; Arabizi translation; Arabic dialects; Arabic lemmatization; and building and evaluating linguistic resources. This book is a valuable reference for scientists, researchers, and students from academia and industry interested in computational linguistics and artificial intelligence, especially for Arabic linguistics and related areas.

ISBN: 9783030346140

Standard No.: 10.1007/978-3-030-34614-0doiSubjects--Topical Terms:

565309
Natural language processing (Computer science)

LC Class. No.: QA76.9.N38 / R434 2020

Dewey Class. No.: 006.35

Recent advances in NLP = the case of Arabic Language /
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520 $a In light of the rapid rise of new trends and applications in various natural language processing tasks, this book presents high-quality research in the field. Each chapter addresses a common challenge in a theoretical or applied aspect of intelligent natural language processing related to Arabic language. Many challenges encountered during the development of the solutions can be resolved by incorporating language technology and artificial intelligence. The topics covered include machine translation; speech recognition; morphological, syntactic, and semantic processing; information retrieval; text classification; text summarization; sentiment analysis; ontology construction; Arabizi translation; Arabic dialects; Arabic lemmatization; and building and evaluating linguistic resources. This book is a valuable reference for scientists, researchers, and students from academia and industry interested in computational linguistics and artificial intelligence, especially for Arabic linguistics and related areas.
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