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Case-Based Reasoning Research and Development

Overview of attention for book
Cover of 'Case-Based Reasoning Research and Development'

Table of Contents

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    Book Overview
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    Chapter 1 The Virtue of Reward: Performance, Reinforcement and Discovery in Case-Based Reasoning
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    Chapter 2 Learning to Optimize Plan Execution in Information Agents
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    Chapter 3 Cased-Based Reasoning by Human Experts
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    Chapter 4 Learning to Win: Case-Based Plan Selection in a Real-Time Strategy Game
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    Chapter 5 An Ensemble of Case-Based Classifiers for High-Dimensional Biological Domains
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    Chapter 6 Language Games: Solving the Vocabulary Problem in Multi-Case-Base Reasoning
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    Chapter 7 Evaluation and Monitoring of the Air-Sea Interaction Using a CBR-Agents Approach
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    Chapter 8 A Comparative Analysis of Query Similarity Metrics for Community-Based Web Search
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    Chapter 9 A Case-Based Approach for Indoor Location
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    Chapter 10 P2P Case Retrieval with an Unspecified Ontology
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    Chapter 11 Autonomous Internal Control System for Small to Medium Firms
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    Chapter 12 The Application of a Case-Based Reasoning System to Attention-Deficit Hyperactivity Disorder
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    Chapter 13 Reasoning with Textual Cases
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    Chapter 14 Using Ensembles of Binary Case-Based Reasoners
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    Chapter 15 Transfer in Visual Case-Based Problem Solving
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    Chapter 16 Generating Estimates of Classification Confidence for a Case-Based Spam Filter
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    Chapter 17 Improving Gene Selection in Microarray Data Analysis Using Fuzzy Patterns Inside a CBR System
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    Chapter 18 CBR for State Value Function Approximation in Reinforcement Learning
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    Chapter 19 Using CBR to Select Solution Strategies in Constraint Programming
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    Chapter 20 Case-Based Art
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    Chapter 21 Supporting Conversation Variability in COBBER Using Causal Loops
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    Chapter 22 Opportunities for CBR in Learning by Doing
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    Chapter 23 Navigating Through Case Base Competence
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    Chapter 24 A Knowledge-Intensive Method for Conversational CBR
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    Chapter 25 Re-using Implicit Knowledge in Short-Term Information Profiles for Context-Sensitive Tasks
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    Chapter 26 Acquiring Similarity Cases for Classification Problems
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    Chapter 27 A Live-User Evaluation of Incremental Dynamic Critiquing
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    Chapter 28 Case Based Representation and Retrieval with Time Dependent Features
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    Chapter 29 The Best Way to Instil Confidence Is by Being Right
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    Chapter 30 Cooperative Reuse for Compositional Cases in Multi-agent Systems
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    Chapter 31 Evaluating the Effectiveness of Exploration and Accumulated Experience in Automatic Case Elicitation
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    Chapter 32 HYREC: A Hybrid Recommendation System for E-Commerce
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    Chapter 33 Extending jCOLIBRI for Textual CBR
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    Chapter 34 Critiquing with Confidence
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    Chapter 35 Mapping Goals and Kinds of Explanations to the Knowledge Containers of Case-Based Reasoning Systems
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    Chapter 36 An Approach for Temporal Case-Based Reasoning: Episode-Based Reasoning
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    Chapter 37 How to Combine CBR and RBR for Diagnosing Multiple Medical Disorder Cases
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    Chapter 38 Case-Based Student Modeling Using Concept Maps
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    Chapter 39 Learning Similarity Measures: A Formal View Based on a Generalized CBR Model
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    Chapter 40 Knowledge-Rich Similarity-Based Classification
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    Chapter 41 Autonomous Creation of New Situation Cases in Structured Continuous Domains
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    Chapter 42 Retrieval and Configuration of Life Insurance Policies
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    Chapter 43 Analogical and Case-Based Reasoning for Predicting Satellite Task Schedulability
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    Chapter 44 Case Adaptation by Segment Replanning for Case-Based Planning Systems
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    Chapter 45 Selecting the Best Units in a Fleet: Performance Prediction from Equipment Peers
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    Chapter 46 CCBR–Driven Business Process Evolution
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    Chapter 47 CBR for Modeling Complex Systems
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    Chapter 48 CBE-Conveyor : A Case-Based Reasoning System to Assist Engineers in Designing Conveyor Systems
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

3 patents
1 Wikipedia page


4 Dimensions

Readers on

16 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Case-Based Reasoning Research and Development
Published by
Lecture notes in computer science, January 2005
DOI 10.1007/11536406
978-3-54-028174-0, 978-3-54-031855-2

Héctor Muñoz-Ávila, Francesco Ricci


Munoz-Avila, Hector, Ricci, Francesco

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 13%
Student > Postgraduate 1 6%
Student > Master 1 6%
Unknown 12 75%
Readers by discipline Count As %
Computer Science 2 13%
Psychology 1 6%
Engineering 1 6%
Unknown 12 75%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 July 2010.
All research outputs
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Outputs from Lecture notes in computer science
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Outputs of similar age
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Outputs of similar age from Lecture notes in computer science
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Altmetric has tracked 9,295,130 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,859 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 83% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 224,303 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 95 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.