Sentiment Analysis and Ontology Engineering An Environment of Computational Intelligence

Sentiment Analysis and Ontology Engineering An Environment of Computational Intelligence / edited by Witold Pedrycz, Shyi-Ming Chen.

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Pedrycz, Witold (Editor), Chen, Shyi-Ming (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edition:1st ed. 2016.
Series:Studies in Computational Intelligence, 639
Springer eBook Collection.
Subjects:
Computational intelligence.
Artificial intelligence.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 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.

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