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Case-Based Reasoning Research and Development

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Cover of 'Case-Based Reasoning Research and Development'

Table of Contents

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    Book Overview
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    Chapter 1 Using Case-Based Reasoning for Capturing Expert Knowledge on Explanation Methods
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    Chapter 2 A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations
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    Chapter 3 How Close Is Too Close? The Role of Feature Attributions in Discovering Counterfactual Explanations
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    Chapter 4 Algorithmic Bias and Fairness in Case-Based Reasoning
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    Chapter 5 “Better” Counterfactuals, Ones People Can Understand: Psychologically-Plausible Case-Based Counterfactuals Using Categorical Features for Explainable AI (XAI)
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    Chapter 6 Extracting Case Indices from Convolutional Neural Networks: A Comparative Study
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    Chapter 7 Exploring the Effect of Recipe Representation on Critique-Based Conversational Recommendation
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    Chapter 8 Explaining CBR Systems Through Retrieval and Similarity Measure Visualizations: A Case Study
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    Chapter 9 Adapting Semantic Similarity Methods for Case-Based Reasoning in the Cloud
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    Chapter 10 Case Adaptation with Neural Networks: Capabilities and Limitations
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    Chapter 11 A Deep Learning Approach to Solving Morphological Analogies
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    Chapter 12 Theoretical and Experimental Study of a Complexity Measure for Analogical Transfer
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    Chapter 13 Case-Based Learning and Reasoning Using Layered Boundary Multigraphs
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    Chapter 14 Particle Swarm Optimization in Small Case Bases for Software Effort Estimation
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    Chapter 15 MicroCBR: Case-Based Reasoning on Spatio-temporal Fault Knowledge Graph for Microservices Troubleshooting
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    Chapter 16 GPU-Based Graph Matching for Accelerating Similarity Assessment in Process-Oriented Case-Based Reasoning
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    Chapter 17 Never Judge a Case by Its (Unreliable) Neighbors: Estimating Case Reliability for CBR
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    Chapter 18 Improving Automated Hyperparameter Optimization with Case-Based Reasoning
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    Chapter 19 A Factorial Study of Neural Network Learning from Differences for Regression
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    Chapter 20 Case-Based Inverse Reinforcement Learning Using Temporal Coherence
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    Chapter 21 Analogy-Based Post-treatment of CNN Image Segmentations
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    Chapter 22 An Extended Case-Based Approach to Race-Time Prediction for Recreational Marathon Runners
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    Chapter 23 A Case-Based Reasoning Approach to Plugin Parameter Selection in Vocal Audio Production
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    Chapter 24 Forecasting for Sustainable Dairy Produce: Enhanced Long-Term, Milk-Supply Forecasting Using k -NN for Data Augmentation, with Prefactual Explanations for XAI
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    Chapter 25 A Case-Based Approach for Content Planning in Data-to-Text Generation
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    Chapter 26 The Use of Computer-Assisted Case-Based Reasoning to Support Clinical Decision-Making – A Scoping Review
Attention for Chapter 4: Algorithmic Bias and Fairness in Case-Based Reasoning
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Chapter title
Algorithmic Bias and Fairness in Case-Based Reasoning
Chapter number 4
Book title
Case-Based Reasoning Research and Development
Published by
Springer, Cham, August 2022
DOI 10.1007/978-3-031-14923-8_4
Book ISBNs
978-3-03-114922-1, 978-3-03-114923-8
Authors

William Blanzeisky, Barry Smyth, Pádraig Cunningham, Blanzeisky, William, Smyth, Barry, Cunningham, Pádraig

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 1 100%
Readers by discipline Count As %
Computer Science 1 100%