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Sentiment Analysis and Ontology Engineering An Environment of Computational Intelligence

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Beschreibung

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....

Beschreibung

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. 

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.04.2018

Abbildungen

X, 456 p. 103 illus., 73 illus. in color.

Herausgeber Witold Pedrycz + weitere

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.04.2018

Abbildungen

X, 456 p. 103 illus., 73 illus. in color.

Herausgeber
Verlag Springer
Seitenzahl

456

Maße (L/B/H)

23,5/15,5/2,6 cm

Gewicht

703 g

Auflage

Softcover reprint of the original 1st ed. 2016

Sprache

Englisch

ISBN

978-3-319-80779-9

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Sentiment Analysis and Ontology Engineering
  • Produktbild: Sentiment Analysis and Ontology Engineering

  • 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 SVM

    perf.- 

    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.