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Machine Learning and Knowledge Extraction

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Cover of 'Machine Learning and Knowledge Extraction'

Table of Contents

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    Book Overview
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    Chapter 1 Current Advances, Trends and Challenges of Machine Learning and Knowledge Extraction: From Machine Learning to Explainable AI
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    Chapter 2 A Modified Particle Swarm Optimization Algorithm for Community Detection in Complex Networks
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    Chapter 3 Mouse Tracking Measures and Movement Patterns with Application for Online Surveys
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    Chapter 4 Knowledge Compilation Techniques for Model-Based Diagnosis of Complex Active Systems
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    Chapter 5 Recognition of Handwritten Characters Using Google Fonts and Freeman Chain Codes
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    Chapter 6 An Efficient Approach for Extraction Positive and Negative Association Rules from Big Data
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    Chapter 7 Field-Reliability Predictions Based on Statistical System Lifecycle Models
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    Chapter 8 Building a Knowledge Based Summarization System for Text Data Mining
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    Chapter 9 Spanish Twitter Data Used as a Source of Information About Consumer Food Choice
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    Chapter 10 Feedback Matters! Predicting the Appreciation of Online Articles A Data - Driven Approach
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    Chapter 11 Creative Intelligence – Automating Car Design Studio with Generative Adversarial Networks (GAN)
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    Chapter 12 A Combined CNN and LSTM Model for Arabic Sentiment Analysis
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    Chapter 13 Between the Lines: Machine Learning for Prediction of Psychological Traits - A Survey
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    Chapter 14 LawStats – Large-Scale German Court Decision Evaluation Using Web Service Classifiers
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    Chapter 15 Clinical Text Mining for Context Sequences Identification
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    Chapter 16 A Multi-device Assistive System for Industrial Maintenance Operations
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    Chapter 17 Feedback Presentation for Workers in Industrial Environments – Challenges and Opportunities
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    Chapter 18 On a New Method to Build Group Equivariant Operators by Means of Permutants
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    Chapter 19 Topological Characteristics of Digital Models of Geological Core
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    Chapter 20 Shortened Persistent Homology for a Biomedical Retrieval System with Relevance Feedback
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    Chapter 21 Explainable AI: The New 42?
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    Chapter 22 A Rule Extraction Study Based on a Convolutional Neural Network
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    Chapter 23 Evaluating Explanations by Cognitive Value
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    Chapter 24 Measures of Model Interpretability for Model Selection
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    Chapter 25 Regular Inference on Artificial Neural Networks
Attention for Chapter 25: Regular Inference on Artificial Neural Networks
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