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Sentiment Analysis and Ontology Engineering: An Environment of Computational Intelligence
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.
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.
826 pages, Kindle Edition
Published March 22, 2016
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