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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Computational Intelligence Applications for Text and Sentiment Data Analysis
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
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Add to basketPAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Computational Intelligence Applications for Text and Sentiment Data Analysis
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Computational Intelligence Applications for Text and Sentiment Data Analysis (Hybrid Computational Intelligence for Pattern Analysis and Understanding)
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Computational Intelligence Applications for Text and Sentiment Data Analysis
Published by Elsevier Science & Technology, 2023
ISBN 10: 0323905358 ISBN 13: 9780323905350
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Add to basketPaperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 450.
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Computational Intelligence Applications for Text and Sentiment Data Analysis
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US$ 186.31
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Computational Intelligence Applications for Text and Sentiment Data Analysis
Published by Elsevier Science & Technology, 2023
ISBN 10: 0323905358 ISBN 13: 9780323905350
Language: English
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
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Computational Intelligence Applications for Text and Sentiment Data Analysis
Published by Elsevier Science & Technology Jul 2023, 2023
ISBN 10: 0323905358 ISBN 13: 9780323905350
Language: English
US$ 179.35
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Add to basketTaschenbuch. Condition: Neu. Neuware - Computational Intelligence Applications for Text and Sentiment Data Analysis explores the most recent advances in text information processing and data analysis technologies, specifically focusing on sentiment analysis from multifaceted data. The book investigates a wide range of challenges involved in the accurate analysis of online sentiments, including how to i) identify subjective information from text, i.e., exclusion of 'neutral' or 'factual' comments that do not carry sentiment information, ii) identify sentiment polarity, and iii) domain dependency. Spam and fake news detection, short abbreviation, sarcasm, word negation, and a lot of word ambiguity are also explored. Further chapters look at the difficult process of extracting sentiment from different multimodal information (audio, video and text), semantic concepts. In each chapter, the book's authors explore how computational intelligence (CI) techniques, such as deep learning, convolutional neural network, fuzzy and rough set, global optimizers, and hybrid machine learning techniques play an important role in solving the inherent problems of sentiment analysis applications.
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Computational Intelligence Applications for Text and Sentiment Data Analysis
Published by Elsevier Science & Technology, 2023
ISBN 10: 0323905358 ISBN 13: 9780323905350
Language: English
Condition: New. 2023. Paperback. . . . . . Books ship from the US and Ireland.
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Computational Intelligence Applications for Text and Sentiment Data Analysis
Published by Elsevier Science and Technology, GB, 2023
ISBN 10: 0323905358 ISBN 13: 9780323905350
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
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US$ 231.86
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Add to basketPaperback. Condition: New. Computational Intelligence Applications for Text and Sentiment Data Analysis explores the most recent advances in text information processing and data analysis technologies, specifically focusing on sentiment analysis from multifaceted data. The book investigates a wide range of challenges involved in the accurate analysis of online sentiments, including how to i) identify subjective information from text, i.e., exclusion of 'neutral' or 'factual' comments that do not carry sentiment information, ii) identify sentiment polarity, and iii) domain dependency. Spam and fake news detection, short abbreviation, sarcasm, word negation, and a lot of word ambiguity are also explored.Further chapters look at the difficult process of extracting sentiment from different multimodal information (audio, video and text), semantic concepts. In each chapter, the book's authors explore how computational intelligence (CI) techniques, such as deep learning, convolutional neural network, fuzzy and rough set, global optimizers, and hybrid machine learning techniques play an important role in solving the inherent problems of sentiment analysis applications.
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Kernel-based Data Fusion for Machine Learning: Methods and Applications in Bioinformatics and Text Mining (Studies in Computational Intelligence, 345)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Kernel-based Data Fusion for Machine Learning: Methods and Applications in Bioinformatics and Text Mining (Studies in Computational Intelligence, 345)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
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Add to basketHardcover. Condition: Like New. Like New. book.
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Computational Intelligence Applications for Text and Sentiment Data Analysis
Published by Elsevier Science and Technology, GB, 2023
ISBN 10: 0323905358 ISBN 13: 9780323905350
Language: English
US$ 218.39
Convert currencyUS$ 88.84 shipping from United Kingdom to U.S.A.Quantity: 1 available
Add to basketPaperback. Condition: New. Computational Intelligence Applications for Text and Sentiment Data Analysis explores the most recent advances in text information processing and data analysis technologies, specifically focusing on sentiment analysis from multifaceted data. The book investigates a wide range of challenges involved in the accurate analysis of online sentiments, including how to i) identify subjective information from text, i.e., exclusion of 'neutral' or 'factual' comments that do not carry sentiment information, ii) identify sentiment polarity, and iii) domain dependency. Spam and fake news detection, short abbreviation, sarcasm, word negation, and a lot of word ambiguity are also explored.Further chapters look at the difficult process of extracting sentiment from different multimodal information (audio, video and text), semantic concepts. In each chapter, the book's authors explore how computational intelligence (CI) techniques, such as deep learning, convolutional neural network, fuzzy and rough set, global optimizers, and hybrid machine learning techniques play an important role in solving the inherent problems of sentiment analysis applications.
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US$ 297.04
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US$ 319.37
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Add to basketHardcover. Condition: Brand New. 212 pages. 9.25x6.25x0.25 inches. In Stock.
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US$ 143.13
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US$ 156.36
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Add to basketPaperback. Condition: Brand New. 350 pages. 9.00x6.00x0.61 inches. In Stock. This item is printed on demand.
