Elsevier Science & Technology
Elsevier Science & Technology - Computational Intelligence Applications For Text And Sentiment Data Analysis - Paperback
Elsevier Science & Technology - Computational Intelligence Applications For Text And Sentiment Data Analysis - Paperback
Books
Regular price
$170.30 USD
Regular price
Sale price
$170.30 USD
Unit price
per
Shipping calculated at checkout.
Couldn't load pickup availability
Binding: Paperback
Description: 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.
Title: Computational Intelligence Applications For Text And Sentiment Data Analysis
Brand: Elsevier Science & Technology
Barcode: 9780323905350
Pages: 270 Pages
Publication Date: 7/20/2023
Series: Hybrid Computational Intelligence for Pattern Analysis and Understanding
Category: Artificial Intelligence
Description: 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.
Title: Computational Intelligence Applications For Text And Sentiment Data Analysis
Brand: Elsevier Science & Technology
Barcode: 9780323905350
Pages: 270 Pages
Publication Date: 7/20/2023
Series: Hybrid Computational Intelligence for Pattern Analysis and Understanding
Category: Artificial Intelligence
