國立虎尾科技大學 |

Sentiment Analysis and Ontology Engineering = An Environment of Computational Intelligence /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Sentiment Analysis and Ontology Engineering/ edited by Witold Pedrycz, Shyi-Ming Chen.
Reminder of title:	An Environment of Computational Intelligence /
other author:	Pedrycz, Witold.
Description:	X, 456 p. 103 illus., 73 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computational intelligence. -
Online resource:	https://doi.org/10.1007/978-3-319-30319-2
ISBN:	9783319303192

Sentiment Analysis and Ontology Engineering = An Environment of Computational Intelligence /
Sentiment Analysis and Ontology EngineeringAn Environment of Computational Intelligence /[electronic resource] :edited by Witold Pedrycz, Shyi-Ming Chen. - 1st ed. 2016. - X, 456 p. 103 illus., 73 illus. in color.online resource. - Studies in Computational Intelligence,6391860-949X ;. - Studies in Computational Intelligence,564.

Fundamentals of Sentiment Analysis and Its Applications -- Fundamentals of Sentiment Analysis: Concepts and Methodology -- The Comprehension of Figurative Language: What is the Influence of Irony and Sarcasm on NLP Techniques? -- Probabilistic Approaches for Sentiment Analysis: Latent Dirichlet Allocation for Ontology Building and Sentiment Extraction -- Description Logic Class Expression Learning Applied to Sentiment Analysis -- Capturing Digest Emotions by Means of Fuzzy Linguistic Aggregation -- Hyperelastic-based Adaptive Dynamics Methodology in Knowledge Acquisition for Computational Intelligence on Ontology Engineering of Evolving Folksonomy Driven Environment -- Sentiment-Oriented Information Retrieval: Affective Analysis of Documents Based on the SenticNet Framework -- Interpretability of Computational Models for Sentiment Analysis -- Chinese Micro-blog Emotion Classification by Exploiting Linguistic Features and SVMperf -- Social Media and News Sentiment Analysis for Advanced Investment Strategies -- Context Aware Customer Experience Management: A Development Framework Based on Ontologies and Computational Intelligence -- An Overview of Sentiment Analysis in Social Media and Its Applications in Disaster Relief -- Big Data Sentiment Analysis for Brand Monitoring in Social Media Streams by Cloud Computing -- Neuro-Fuzzy Sentiment Analysis for Customer Review Rating Prediction -- OntoLSA: An Integrated Text Mining System for Ontology Learning and Sentiment Analysis -- Knowledge-based Tweet Classification for Disease Sentiment Monitoring.

This edited volume provides the reader with a fully updated, in-depth treatise on the emerging principles, conceptual underpinnings, algorithms and practice of Computational Intelligence in the realization of concepts and implementation of models of sentiment analysis and ontology –oriented engineering. The volume involves studies devoted to key issues of sentiment analysis, sentiment models, and ontology engineering. The book is structured into three main parts. The first part offers a comprehensive and prudently structured exposure to the fundamentals of sentiment analysis and natural language processing. The second part consists of studies devoted to the concepts, methodologies, and algorithmic developments elaborating on fuzzy linguistic aggregation to emotion analysis, carrying out interpretability of computational sentiment models, emotion classification, sentiment-oriented information retrieval, a methodology of adaptive dynamics in knowledge acquisition. The third part includes a plethora of applications showing how sentiment analysis and ontologies becomes successfully applied to investment strategies, customer experience management, disaster relief, monitoring in social media, customer review rating prediction, and ontology learning. This book is aimed at a broad audience of researchers and practitioners. Readers involved in intelligent systems, data analysis, Internet engineering, Computational Intelligence, and knowledge-based systems will benefit from the exposure to the subject matter. The book may also serve as a highly useful reference material for graduate students and senior undergraduate students. .

ISBN: 9783319303192

Standard No.: 10.1007/978-3-319-30319-2doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Sentiment Analysis and Ontology Engineering = An Environment of Computational Intelligence /
LDR:04674nam a22004095i 4500 001 974691
003 DE-He213
005 20200706024453.0
007 cr nn 008mamaa
008 201211s2016 gw | s |||| 0|eng d
020 $a 9783319303192 $9 978-3-319-30319-2
024 7 $a 10.1007/978-3-319-30319-2 $2 doi
035 $a 978-3-319-30319-2
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
245 1 0 $a Sentiment Analysis and Ontology Engineering $h [electronic resource] : $b An Environment of Computational Intelligence / $c edited by Witold Pedrycz, Shyi-Ming Chen.
250 $a 1st ed. 2016.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a X, 456 p. 103 illus., 73 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Studies in Computational Intelligence, $x 1860-949X ; $v 639
505 0 $a Fundamentals of Sentiment Analysis and Its Applications -- Fundamentals of Sentiment Analysis: Concepts and Methodology -- The Comprehension of Figurative Language: What is the Influence of Irony and Sarcasm on NLP Techniques? -- Probabilistic Approaches for Sentiment Analysis: Latent Dirichlet Allocation for Ontology Building and Sentiment Extraction -- Description Logic Class Expression Learning Applied to Sentiment Analysis -- Capturing Digest Emotions by Means of Fuzzy Linguistic Aggregation -- Hyperelastic-based Adaptive Dynamics Methodology in Knowledge Acquisition for Computational Intelligence on Ontology Engineering of Evolving Folksonomy Driven Environment -- Sentiment-Oriented Information Retrieval: Affective Analysis of Documents Based on the SenticNet Framework -- Interpretability of Computational Models for Sentiment Analysis -- Chinese Micro-blog Emotion Classification by Exploiting Linguistic Features and SVMperf -- Social Media and News Sentiment Analysis for Advanced Investment Strategies -- Context Aware Customer Experience Management: A Development Framework Based on Ontologies and Computational Intelligence -- An Overview of Sentiment Analysis in Social Media and Its Applications in Disaster Relief -- Big Data Sentiment Analysis for Brand Monitoring in Social Media Streams by Cloud Computing -- Neuro-Fuzzy Sentiment Analysis for Customer Review Rating Prediction -- OntoLSA: An Integrated Text Mining System for Ontology Learning and Sentiment Analysis -- Knowledge-based Tweet Classification for Disease Sentiment Monitoring.
520 $a This edited volume provides the reader with a fully updated, in-depth treatise on the emerging principles, conceptual underpinnings, algorithms and practice of Computational Intelligence in the realization of concepts and implementation of models of sentiment analysis and ontology –oriented engineering. The volume involves studies devoted to key issues of sentiment analysis, sentiment models, and ontology engineering. The book is structured into three main parts. The first part offers a comprehensive and prudently structured exposure to the fundamentals of sentiment analysis and natural language processing. The second part consists of studies devoted to the concepts, methodologies, and algorithmic developments elaborating on fuzzy linguistic aggregation to emotion analysis, carrying out interpretability of computational sentiment models, emotion classification, sentiment-oriented information retrieval, a methodology of adaptive dynamics in knowledge acquisition. The third part includes a plethora of applications showing how sentiment analysis and ontologies becomes successfully applied to investment strategies, customer experience management, disaster relief, monitoring in social media, customer review rating prediction, and ontology learning. This book is aimed at a broad audience of researchers and practitioners. Readers involved in intelligent systems, data analysis, Internet engineering, Computational Intelligence, and knowledge-based systems will benefit from the exposure to the subject matter. The book may also serve as a highly useful reference material for graduate students and senior undergraduate students. .
650 0 $a Computational intelligence. $3 568984
650 0 $a Artificial intelligence. $3 559380
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Artificial Intelligence. $3 646849
700 1 $a Pedrycz, Witold. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 678017
700 1 $a Chen, Shyi-Ming. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 785891
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319303178
776 0 8 $i Printed edition: $z 9783319303185
776 0 8 $i Printed edition: $z 9783319807799
830 0 $a Studies in Computational Intelligence, $x 1860-949X ; $v 564 $3 1253640
856 4 0 $u https://doi.org/10.1007/978-3-319-30319-2
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)