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Sentiment Analysis and Ontology Engineering

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Cover of 'Sentiment Analysis and Ontology Engineering'

Table of Contents

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    Book Overview
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    Chapter 1 Fundamentals of Sentiment Analysis and Its Applications
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    Chapter 2 Fundamentals of Sentiment Analysis: Concepts and Methodology
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    Chapter 3 The Comprehension of Figurative Language: What Is the Influence of Irony and Sarcasm on NLP Techniques?
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    Chapter 4 Probabilistic Approaches for Sentiment Analysis: Latent Dirichlet Allocation for Ontology Building and Sentiment Extraction
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    Chapter 5 Description Logic Class Expression Learning Applied to Sentiment Analysis
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    Chapter 6 Capturing Digest Emotions by Means of Fuzzy Linguistic Aggregation
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    Chapter 7 Hyperelastic-Based Adaptive Dynamics Methodology in Knowledge Acquisition for Computational Intelligence on Ontology Engineering of Evolving Folksonomy Driven Environment
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    Chapter 8 Sentiment-Oriented Information Retrieval: Affective Analysis of Documents Based on the SenticNet Framework
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    Chapter 9 Interpretability of Computational Models for Sentiment Analysis
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    Chapter 10 Chinese Micro-Blog Emotion Classification by Exploiting Linguistic Features and SVM \(^{\textit{perf}}\)
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    Chapter 11 Social Media and News Sentiment Analysis for Advanced Investment Strategies
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    Chapter 12 Context Aware Customer Experience Management: A Development Framework Based on Ontologies and Computational Intelligence
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    Chapter 13 An Overview of Sentiment Analysis in Social Media and Its Applications in Disaster Relief
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    Chapter 14 Big Data Sentiment Analysis for Brand Monitoring in Social Media Streams by Cloud Computing
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    Chapter 15 Neuro-Fuzzy Sentiment Analysis for Customer Review Rating Prediction
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    Chapter 16 OntoLSA—An Integrated Text Mining System for Ontology Learning and Sentiment Analysis
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    Chapter 17 Knowledge-Based Tweet Classification for Disease Sentiment Monitoring
Attention for Chapter 14: Big Data Sentiment Analysis for Brand Monitoring in Social Media Streams by Cloud Computing
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