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Advances in case-based reasoning : 6th European conference, ECCBR 2002, Aberdeen, Scotland, UK, September 4-7, 2002, proceedings / / edited by Susan Craw, Alun Preece
| Advances in case-based reasoning : 6th European conference, ECCBR 2002, Aberdeen, Scotland, UK, September 4-7, 2002, proceedings / / edited by Susan Craw, Alun Preece |
| Edizione | [1st ed. 2002.] |
| Pubbl/distr/stampa | Berlin, Germany ; ; New York, New York : , : Springer, , [2002] |
| Descrizione fisica | 1 online resource (XII, 656 p.) |
| Disciplina | 006.33 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Expert systems (Computer science)
Case-based reasoning |
| ISBN | 3-540-46119-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Integrating Background Knowledge into Nearest-Neighbor Text Classification -- Applying Knowledge Management: Techniques for Building Organisational Memories -- Research Papers -- On the Complexity of Plan Adaptation by Derivational Analogy in a Universal Classical Planning Framework -- Inductive Learning for Case-Based Diagnosis with Multiple Faults -- Diverse Product Recommendations Using an Expressive Language for Case Retrieval -- Digital Image Similarity for Geo-spatial Knowledge Management -- Poetry Generation in COLIBRI -- Adaptation Using Iterated Estimations -- The Use of a Uniform Declarative Model in 3D Visualisation for Case-Based Reasoning -- Experiments on Case-Based Retrieval of Software Designs -- Exploiting Taxonomic and Causal Relations in Conversational Case Retrieval -- Bayesian Case Reconstruction -- Relations between Customer Requirements, Performance Measures, and General Case Properties for Case Base Maintenance -- Representing Temporal Knowledge for Case-Based Prediction -- Local Predictions for Case-Based Plan Recognition -- Automatically Selecting Strategies for Multi-Case-Base Reasoning -- Diversity-Conscious Retrieval -- Improving Case Representation and Case Base Maintenance in Recommender Agents -- Similarity Assessment for Generalizied Cases by Optimization Methods -- Case Acquisition in a Project Planning Environment -- Improving Case-Based Recommendation -- Efficient Similarity Determination and Case Construction Techniques for Case-Based Reasoning -- Constructive Adaptation -- A Fuzzy Case Retrieval Approach Based on SQL for Implementing Electronic Catalogs -- Integrating Hybrid Rule-Based with Case-Based Reasoning -- Search and Adaptation in a Fuzzy Object Oriented Case Base -- Deleting and Building Sort Out Techniques for Case Base Maintenance -- Entropy-Based vs. Similarity-Influenced: Attribute Selection Methods for Dialogs Tested on Different Electronic Commerce Domains -- Category-Based Filtering and User Stereotype Cases to Reduce the Latency Problem in Recommender Systems -- Defining Similarity Measures: Top-Down vs. Bottom-Up -- Learning to Adapt for Case-Based Design -- An Approach to Aggregating Ensembles of Lazy Learners That Supports Explanation -- An Experimental Study of Increasing Diversity for Case-Based Diagnosis -- Application Papers -- Collaborative Case-Based Recommender Systems -- Tuning Production Processes through a Case Based Reasoning Approach -- An Application of Case-Based Reasoning to the Adaptive Management of Wireless Networks -- A Case-Based Personal Travel Assistant for Elaborating User Requirements and Assessing Offers -- An Automated Hybrid CBR System for Forecasting -- Using CBR for Automation of Software Design Patterns -- A New Approach to Solution Adaptation and Its Application for Design Purposes -- InfoFrax: CBR in Fused Cast Refractory Manufacture -- Comparison-Based Recommendation -- Case-Based Reasoning for Estuarine Model Design -- Similarity Guided Learning of the Case Description and Improvement of the System Performance in an Image Classification System -- ITR: A Case-Based Travel Advisory System -- Supporting Electronic Design Reuse by Integrating Quality-Criteria into CBR-Based IP Selection -- Building a Case-Based Decision Support System for Land Development Control Using Land Use Function Pattern. |
| Record Nr. | UNISA-996466336803316 |
| Berlin, Germany ; ; New York, New York : , : Springer, , [2002] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in case-based reasoning : 6th European conference, ECCBR 2002, Aberdeen, Scotland, UK, September 4-7, 2002, proceedings / / edited by Susan Craw, Alun Preece
| Advances in case-based reasoning : 6th European conference, ECCBR 2002, Aberdeen, Scotland, UK, September 4-7, 2002, proceedings / / edited by Susan Craw, Alun Preece |
| Edizione | [1st ed. 2002.] |
| Pubbl/distr/stampa | Berlin, Germany ; ; New York, New York : , : Springer, , [2002] |
| Descrizione fisica | 1 online resource (XII, 656 p.) |
| Disciplina | 006.33 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Expert systems (Computer science)
Case-based reasoning |
| ISBN | 3-540-46119-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Integrating Background Knowledge into Nearest-Neighbor Text Classification -- Applying Knowledge Management: Techniques for Building Organisational Memories -- Research Papers -- On the Complexity of Plan Adaptation by Derivational Analogy in a Universal Classical Planning Framework -- Inductive Learning for Case-Based Diagnosis with Multiple Faults -- Diverse Product Recommendations Using an Expressive Language for Case Retrieval -- Digital Image Similarity for Geo-spatial Knowledge Management -- Poetry Generation in COLIBRI -- Adaptation Using Iterated Estimations -- The Use of a Uniform Declarative Model in 3D Visualisation for Case-Based Reasoning -- Experiments on Case-Based Retrieval of Software Designs -- Exploiting Taxonomic and Causal Relations in Conversational Case Retrieval -- Bayesian Case Reconstruction -- Relations between Customer Requirements, Performance Measures, and General Case Properties for Case Base Maintenance -- Representing Temporal Knowledge for Case-Based Prediction -- Local Predictions for Case-Based Plan Recognition -- Automatically Selecting Strategies for Multi-Case-Base Reasoning -- Diversity-Conscious Retrieval -- Improving Case Representation and Case Base Maintenance in Recommender Agents -- Similarity Assessment for Generalizied Cases by Optimization Methods -- Case Acquisition in a Project Planning Environment -- Improving Case-Based Recommendation -- Efficient Similarity Determination and Case Construction Techniques for Case-Based Reasoning -- Constructive Adaptation -- A Fuzzy Case Retrieval Approach Based on SQL for Implementing Electronic Catalogs -- Integrating Hybrid Rule-Based with Case-Based Reasoning -- Search and Adaptation in a Fuzzy Object Oriented Case Base -- Deleting and Building Sort Out Techniques for Case Base Maintenance -- Entropy-Based vs. Similarity-Influenced: Attribute Selection Methods for Dialogs Tested on Different Electronic Commerce Domains -- Category-Based Filtering and User Stereotype Cases to Reduce the Latency Problem in Recommender Systems -- Defining Similarity Measures: Top-Down vs. Bottom-Up -- Learning to Adapt for Case-Based Design -- An Approach to Aggregating Ensembles of Lazy Learners That Supports Explanation -- An Experimental Study of Increasing Diversity for Case-Based Diagnosis -- Application Papers -- Collaborative Case-Based Recommender Systems -- Tuning Production Processes through a Case Based Reasoning Approach -- An Application of Case-Based Reasoning to the Adaptive Management of Wireless Networks -- A Case-Based Personal Travel Assistant for Elaborating User Requirements and Assessing Offers -- An Automated Hybrid CBR System for Forecasting -- Using CBR for Automation of Software Design Patterns -- A New Approach to Solution Adaptation and Its Application for Design Purposes -- InfoFrax: CBR in Fused Cast Refractory Manufacture -- Comparison-Based Recommendation -- Case-Based Reasoning for Estuarine Model Design -- Similarity Guided Learning of the Case Description and Improvement of the System Performance in an Image Classification System -- ITR: A Case-Based Travel Advisory System -- Supporting Electronic Design Reuse by Integrating Quality-Criteria into CBR-Based IP Selection -- Building a Case-Based Decision Support System for Land Development Control Using Land Use Function Pattern. |
| Record Nr. | UNINA-9910768452203321 |
| Berlin, Germany ; ; New York, New York : , : Springer, , [2002] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Case-based reasoning [[electronic resource] ] : processes, suitability and applications / / Antonia M. Leeland, editor
| Case-based reasoning [[electronic resource] ] : processes, suitability and applications / / Antonia M. Leeland, editor |
| Pubbl/distr/stampa | Hauppauge, N.Y., : Nova Science Publishers, c2011 |
| Descrizione fisica | 1 online resource (183 p.) |
| Disciplina | 153.4/3 |
| Altri autori (Persone) | LeelandAntonia M |
| Collana | Engineering tools, techniques and tables |
| Soggetto topico | Case-based reasoning |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-61728-814-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910461654003321 |
| Hauppauge, N.Y., : Nova Science Publishers, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Case-based reasoning [[electronic resource] ] : processes, suitability and applications / / Antonia M. Leeland, editor
| Case-based reasoning [[electronic resource] ] : processes, suitability and applications / / Antonia M. Leeland, editor |
| Pubbl/distr/stampa | Hauppauge, N.Y., : Nova Science Publishers, c2011 |
| Descrizione fisica | 1 online resource (183 p.) |
| Disciplina | 153.4/3 |
| Altri autori (Persone) | LeelandAntonia M |
| Collana | Engineering tools, techniques and tables |
| Soggetto topico | Case-based reasoning |
| ISBN | 1-61728-814-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910790280303321 |
| Hauppauge, N.Y., : Nova Science Publishers, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Case-based reasoning : processes, suitability and applications / / Antonia M. Leeland, editor
| Case-based reasoning : processes, suitability and applications / / Antonia M. Leeland, editor |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Hauppauge, N.Y., : Nova Science Publishers, c2011 |
| Descrizione fisica | 1 online resource (183 p.) |
| Disciplina | 153.4/3 |
| Altri autori (Persone) | LeelandAntonia M |
| Collana | Engineering tools, techniques and tables |
| Soggetto topico | Case-based reasoning |
| ISBN | 1-61728-814-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- CASE-BASED REASONING: PROCESSES, SUITABILITY AND APPLICATIONS -- CASE-BASED REASONING: PROCESSES, SUITABILITY AND APPLICATIONS -- LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA -- CONTENTS -- PREFACE -- Chapter 1 CASE-BASED REASONING INTEGRATIONS: APPROACHES AND APPLICATIONS -- ABSTRACT -- 1. INTRODUCTION -- 2. TRENDS IN INTEGRATIONS OF CBR WITH OTHER INTELLIGENT METHODS -- 3. REPRESENTATIVE SYSTEMS -- 3.1 Sequential Processing Approaches -- 3.1.1 Loosely coupled sequence -- 3.1.2 Tightly coupled sequence -- 3.2. Co-processing Approaches -- 3.2.1 Cooperation oriented -- 3.2.1.1 Explicit reasoning control -- 3.2.1.2 Implicit reasoning control -- 3.2.2 Reconciliation oriented -- 3.3 Embedded Processing -- 4. COMBINATION OF CBR WITH NEURULES -- 4.1 Syntax and Semantics -- 4.2 Indexing and Hybrid Inference -- CONCLUSIONS -- REFERENCES -- Chapter 2 APPLYING IMPROVED CASE INDEXING AND RETRIEVING USING EX-POST INFORMATION IN CORPORATE BANKRUPTCY PREDICTION -- ABSTRACT -- INTRODUCTION -- LITERATURE REVIEW -- Distance Metric -- 1. Linear distance metrics -- 2. Value difference metric -- Feature selection & -- determining number of cases -- Weighting features -- PROPOSED MODEL -- RESEARCH DATA AND EXPERIMENTS -- Step 1. Selecting Observation Firm Set -- Step 2. Categorizing Financial Dimensions -- Step 3. Identifying and Obtaining Candidate Financial Ratios -- Step 4. Selecting Final Financial Ratios -- Step 5. Calculating Efficiencies Using DEA for the Data Set -- Step 6. Determining Case Base -- Step 7. Dividing Experiment Sets -- Step 8. Calculating Feature Weights -- Step 9. Measuring Similarity -- Step 10. Updating Case Base -- RESULT AND ANALYSIS -- Experiment 1 -- Experiment 2 -- Unsupervised vs. Supervised -- CONCLUSION -- REFERENCES -- Chapter 3 CASE-BASED REASONING: HISTORY, METHODOLOGY AND DEVELOPMENT TRENDS -- ABSTRACT.
INTRODUCTION -- HISTORY OF CBR -- THE STEPS OF THE CBR PROCESS -- MAIN TYPES OF CBR METHODS -- Case-Based Reasoning -- Analogy-Based Reasoning -- Exemplar-Based Reasoning -- Instance-Based Reasoning -- Memory-Based Reasoning -- 5. TOOLS AND APPLICATIONS OF CBR -- 6. DEVELOPMENT TRENDS OF CBR METHODS AND APPLICATIONS -- CONCLUSION -- REFERENCES -- Chapter 4 A TEMPORAL CASE-BASED PROCEDURE FOR CANCELLATION FORECASTING: A CASE STUDY -- ABSTRACT -- 1. INTRODUCTION -- 2. CANCELLATION CURVES -- 2.1. Canceling Patterns before Departure -- 2.2. Cancellation Patterns at Departure -- 3. MODELS -- 3.1. Case-Based Predicting Model (CBP) -- 3.1.1. Similarity evaluation -- 3.1.2. Sample selection -- 3.1.3. Prediction generation -- 3.1.4. Parameter search -- 3.2. Regression Models -- 3.3. Pick up Models -- 4. EMPIRICAL STUDY -- 4.1. The Best Number of Selection -- 4.2. Comparison with a Naïve CBP Variant -- 4.3. Comparison with Four Benchmarks -- 4.4. Distributions of the Estimated Parameters -- CONCLUSION -- ACKNOWLEDGMENT -- REFERENCES -- Chapter 5 PROVISION OF SAFETY FOR TECHNOLOGICAL SYSTEMS WITH THE AID OF CASE-BASED REASONING -- ABSTRACT -- 1. INTRODUCTION -- 2. CONCEPTUALIZATION OF DATA AND KNOWLEDGE -- 3. THE CASE-BASED APPROACH -- 4. IMPLEMENTATION OF THE SOFTWARE -- 5. EXAMPLE OF APPLICATION OF THE SOFTWARE -- CONCLUSION -- REFERENCES -- Chapter 6 MATHEMATIZING THE CASE-BASED REASONING PROCESS -- ABSTRACT -- INTRODUCTION -- THE MARKOV MODEL -- MEASURING THE EFFECTIVENESS OF A CBR SYSTEM -- FUZZY SETS -- A FUZZY MODEL FOR THE REPRESENTATION OF A CBR SYSTEM -- AN APPLICATION OF THE FUZZY MODEL -- CONCLUSION -- REFERENCES -- Chapter 7 PROTOTYPE-BASED REASONING FOR DIAGNOSIS OF DYSMORPHIC SYNDROMES -- ABSTRACT -- 1. INTRODUCTION -- 1.1. Diagnostic Support for Dysmorphic Syndromes -- 1.2. Other Systems. 1.3. Case-Based Reasoning and Prototypicality Measures -- 2. DIAGNOSIS OF DYSMORPHIC SYNDROMES -- 2.1. Prototypicality Measures -- 2.2. Adaptation Rules -- 3. RESULTS -- 3.1. Application of Adaptation Rules -- 3.2. Application of Adaptation Rules -- 3.3. Application of Automatically Acquired Adaptation Rules -- 4. CONCLUSION -- REFERENCES -- Chapter 8 NEW APPROACH OF CASE-BASED REASONING* -- ABSTRACT -- 1. INTRODUCTION -- 2. NEGOTIATION -- 3. DESCRIPTION OF OUR APPROACH -- 3.1. The 3R Model -- Retrieve -- Reuse -- Retain -- 3.2. Real Estate Negotiation According to the 3R Model -- Case -- Case base -- 3.3. The 3R Model Cycle -- 3.3.1. Retrieve -- A) Retrieve 1: Optimal weights search -- B) Optimal weights specification -- B-1) Initialization of the weights -- B-2) Calculation of the similarity distance -- B-3) Adjustment of the weights -- B-4) Calculation of the optimal weights -- B) Retrieve 2: The search for the similar case -- A) Computation of the Similarity Distance in Relation to the Target -- B) Similar Case Retrieval -- 3.3.3. Retain -- 4. MODEL VALIDATION -- 5. CONCLUSION -- REFERENCES -- Commentary FUZZY SETS IN CASE-BASED REASONING -- INDEX. |
| Record Nr. | UNINA-9910974790403321 |
| Hauppauge, N.Y., : Nova Science Publishers, c2011 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Case-based reasoning research and development : 29th International Conference, ICCBR 2021, Salamanca, Spain, September 13-16, 2021 : proceedings / / Antonio A. Sánchez-Ruiz, Michael W. Floyd
| Case-based reasoning research and development : 29th International Conference, ICCBR 2021, Salamanca, Spain, September 13-16, 2021 : proceedings / / Antonio A. Sánchez-Ruiz, Michael W. Floyd |
| Autore | Sánchez-Ruiz Antonio A. |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer International Publishing, , [2021] |
| Descrizione fisica | 1 online resource (337 pages) |
| Disciplina | 006.33 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Expert systems (Computer science)
Case-based reasoning |
| ISBN | 3-030-86957-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- The Bites Eclectic: Critique-Based Conversational Recommendation for Diversity-Focused Meal Planning -- 1 Introduction -- 2 Background -- 2.1 Diversity -- 2.2 Critiquing -- 2.3 Recipe Recommendation and Diversity -- 3 DiversityBite: A Conversational Dynamic Critique-Based Recommender -- 3.1 Recipe Case Representation and Similarity -- 3.2 Diversity-Focused Conversational Critique -- 4 Evaluation for DiversityBite -- 4.1 Recipe Dataset -- 4.2 Evaluation Study -- 4.3 Evaluation Results -- 5 Discussion and Future Work -- References -- Evaluation of Similarity Measures for Flight Simulator Training Scenarios -- 1 Introduction -- 2 Related Work -- 3 Problem Definition: Pilot Competencies and Event Sets -- 4 Case Retrieval of Scenario Event Sets -- 5 Evaluation of Similarity Measures -- 5.1 Experimental Setup -- 5.2 Analysis -- 6 Results and Discussion -- 7 Conclusions -- References -- Instance-Based Counterfactual Explanations for Time Series Classification -- 1 Introduction -- 2 Related Work -- 3 Good Counterfactuals for Time Series: Key Properties -- 4 Native Guide: Counterfactual XAI for Time Series -- 5 Testing Native Guide: Two Comparative Experiments -- 5.1 Experiment 1: Probing Proximity and Sparsity -- 5.2 Experiment 2: Exploring Plausibility and Diversity -- 6 Conclusion and Future Directions -- References -- User Evaluation to Measure the Perception of Similarity Measures in Artworks -- 1 Introduction -- 2 Related Work About Similarity -- 3 Methodology for Learning Similarity Measures Reflecting Human Perceptions -- 3.1 Methodology for Learning Perception Aware Similarity Measures -- 3.2 Profile Definition -- 4 Experiment on the Perception of Similarity for Artworks -- 4.1 Definition of Local Similarity Measures -- 4.2 Data Gathering of Perceived Similarity -- 4.3 Experimental Results.
5 Conclusions and Future Work -- References -- Measuring Financial Time Series Similarity with a View to Identifying Profitable Stock Market Opportunities -- 1 Introduction -- 2 Related Work -- 3 From Prices to Cases -- 4 Similarity in Financial Time Series -- 4.1 The Problem with Correlation -- 4.2 An Adjusted Correlation Metric -- 4.3 A Novel Similarity Metric for Returns-Based Time-Series -- 4.4 Most and Least Similar Cases -- 5 Evaluation -- 5.1 Predicting Monthly Returns -- 5.2 Comparing Trading Strategies -- 6 Conclusion and Future Work -- References -- A Case-Based Reasoning Approach to Predicting and Explaining Running Related Injuries -- 1 Introduction -- 2 Related Work -- 3 CBR for Injury Prediction and Explanation -- 3.1 Representing Training Load -- 3.2 Representing Injury Cases -- 3.3 Balancing the Case Base -- 3.4 Task 1: Predicting Training Breaks -- 3.5 Task 2: Explaining Training Breaks -- 4 Evaluation -- 4.1 Setup -- 4.2 Evaluating Prediction Accuracy -- 4.3 Evaluating Injury Explanations -- 5 Conclusions -- References -- Bayesian Feature Construction for Case-Based Reasoning: Generating Good Checklists -- 1 Introduction -- 2 Related Work -- 3 Case and Problem Definition -- 4 BCBR Framework -- 4.1 Bayesian Inference -- 4.2 Case Base Creation and CBR Engine -- 4.3 Example: NBI Estimates, Case Retrieval and CBR Case -- 5 Experiments -- 5.1 Experimental Setup -- 5.2 Experiment 1: Answer Classification Performance (Baselines) -- 5.3 Experiment 2: Trustworthiness of Constructed Checklists -- 5.4 Experiment 3: Evaluation of Constructed Checklists -- 6 Conclusion -- References -- Revisiting Fast and Slow Thinking in Case-Based Reasoning -- 1 Introduction -- 2 Background -- 3 Feature Selection -- 3.1 Feature Selection for Parsimonious Search -- 3.2 Modelling Desirability of Feature Sets -- 3.3 Brute Force Approach -- 3.4 Greedy Approach. 3.5 Experimental Analysis -- 4 Constraint-Based Switching -- 4.1 Model 2D -- 4.2 Experimental Analysis -- 5 Complexity Measure for Dichotomous Models -- 5.1 Footprint Size -- 5.2 Footprint with Time -- 5.3 Experimental Analysis -- 6 Conclusion and Future Work -- References -- Harmonizing Case Retrieval and Adaptation with Alternating Optimization -- 1 Introduction -- 2 Background -- 3 Alternating Optimization of Retrieval and Adaptation -- 4 Testbed System Design -- 4.1 Loss Function -- 4.2 Testbed Retrieval and Adaptation -- 4.3 Testbed Training and Testing Procedures -- 5 Evaluation -- 5.1 Experimental Settings -- 5.2 Experimental Results -- 6 Guidelines for Applying AO to Train CBR Components -- 7 Future Work -- 8 Conclusion -- References -- Adaptation Knowledge Discovery Using Positive and Negative Cases -- 1 Introduction -- 2 Motivations and Preliminaries -- 2.1 Assumptions and Notations About CBR -- 2.2 Boolean Setting Illustrated with a Boolean Function Example -- 2.3 Itemset Extraction -- 3 Exploiting Case Variations for Adaptation Knowledge Discovery with Positive and Negative Cases -- 4 Experiments on Benchmarks -- 4.1 Experiment Setting and Evaluation Methodology -- 4.2 Congressional Voting Records -- 4.3 Tic Tac Toe Endgame -- 4.4 Cardiac Diagnosis -- 4.5 Car Evaluation -- 4.6 Results and Discussion -- 5 Conclusion -- References -- When Revision-Based Case Adaptation Meets Analogical Extrapolation -- 1 Introduction -- 2 Setting of the Problem and Running Example -- 2.1 A Quick Refresher About Propositional Logic -- 2.2 Notions and Notations Related to CBR -- 2.3 Specification of the Running Example -- 2.4 Analogical Proportions and CBR -- 2.5 Belief Revision and CBR -- 3 Bridging Extrapolation and Revision-Based Adaptation -- 3.1 Reformulating Adaptation by Extrapolation as a Single Case Adaptation. 3.2 A Revision Operator Based on Competence of Case Pairs -- 3.3 An Approach to Adaptation Based on Extrapolation and Revision -- 3.4 Synthesis -- 4 Related Work and Final Remarks -- References -- Inferring Case-Based Reasoners' Knowledge to Enhance Interactivity -- 1 Introduction -- 2 Problem Statement: Interaction with a CBR Agent -- 3 Modeling the User as a Case-Based Reasoner -- 4 Inference of the CBR Parameters -- 4.1 General Principle -- 4.2 Inference of the Parameters for a Deterministic CBR -- 4.3 Probability of Retrieval for kNN -- 4.4 Discussion on the Inference Process -- 5 Application: Teaching Word Inflection -- 5.1 Presentation of the Application -- 5.2 Implementation of a Case-Based Reasoning Learner -- 5.3 Empirical Evaluation -- 6 Conclusion -- References -- A Case-Based Approach for the Selection of Explanation Algorithms in Image Classification -- 1 Introduction -- 2 Background -- 2.1 LIME -- 2.2 Anchors -- 2.3 Integrated Gradients -- 2.4 XRAI -- 3 CBR Process Specification -- 3.1 Case Base Elicitation -- 3.2 Similarity Metrics -- 3.3 Reuse Strategies -- 4 Evaluation -- 5 Conclusions and Future Work -- References -- Towards Richer Realizations of Holographic CBR -- 1 Introduction -- 2 Holographic Case-Based Reasoning -- 3 Methodology -- 3.1 Key Ideas -- 3.2 Holographic CBR Realization Framework -- 4 Results and Interpretations -- 4.1 Comparison with Baseline -- 4.2 Tests for Efficiency -- 5 Conclusions and Future Directions -- References -- Handling Climate Change Using Counterfactuals: Using Counterfactuals in Data Augmentation to Predict Crop Growth in an Uncertain Climate Future -- 1 Introduction -- 1.1 The Problem: Grass Growth Prediction for Sustainable Dairy Farming -- 1.2 Related Work: Counterfactuals from XAI to Data Augmentation -- 1.3 Research Questions and Novelties. 2 Study 1: Predicting Climate Disruption with PBI-CBR -- 2.1 Defining a Class Boundary for Climate Outlier Cases -- 2.2 Experiment 1a: The Contribution of Climate Outliers to Predictions -- 2.3 Experiment 1b: Role of Training Outliers at Values of k -- 3 Study 2: Predicting Climate Disruption with Counterfactuals -- 3.1 A Case-Based Counterfactual Augmentation Algorithm (CFA) -- 3.2 Experiment 2: Using Synthetic Counterfactual Cases to Predict Growth -- 4 Conclusions: Novelties, Explications and Caveats -- References -- A Case-Based Approach to Data-to-Text Generation -- 1 Introduction -- 2 Related Works -- 3 Background -- 4 Methodology -- 4.1 Case-Base Creation -- 4.2 Retrieval and Feature Weighting -- 4.3 Generation -- 5 Experimental Setup -- 5.1 Dataset -- 5.2 Baseline and Benchmark -- 5.3 Evaluation Methods -- 6 Results and Discussion -- 6.1 Comparison with Benchmark and Baseline -- 6.2 Ablation Studies -- 6.3 Qualitative Analysis -- 7 Conclusion and Future Work -- References -- On Combining Knowledge-Engineered and Network-Extracted Features for Retrieval -- 1 Introduction -- 2 Convolutional Neural Networks for Classification -- 3 Related Work -- 4 Bridging Engineered and Network-Extracted Features -- 5 Evaluation -- 5.1 Test Domain and Testbed System -- 5.2 Preliminary Experiments to Set Network Parameters -- 5.3 How Retrieval Accuracy Changes with KE Feature Degradation -- 5.4 How Using KE and NL Features in Concert Affects Accuracy -- 5.5 How Learned Weights Further Influence Retrieval Accuracy -- 6 Ramifications for Explainability -- 7 Conclusions -- References -- Task and Situation Structures for Case-Based Planning -- 1 Introduction -- 2 Task Structure and Planning -- 2.1 Task Structure -- 2.2 Execution of Tasks -- 2.3 Implementation of Our Task Structure -- 2.4 Discussions on Task Structure -- 3 Situation Structure -- 4 Situation Handling. 5 Illustrative Examples. |
| Record Nr. | UNISA-996464529403316 |
Sánchez-Ruiz Antonio A.
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| Cham, Switzerland : , : Springer International Publishing, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Case-based reasoning research and development : 30th International Conference, ICCBR 2022, Nancy, France, September 12-15, 2022, proceedings / / Mark T. Keane, Nirmalie Wiratunga (editors)
| Case-based reasoning research and development : 30th International Conference, ICCBR 2022, Nancy, France, September 12-15, 2022, proceedings / / Mark T. Keane, Nirmalie Wiratunga (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (420 pages) |
| Disciplina | 153.43 |
| Collana | Lecture notes in computer science. Lecture notes in artificial intelligence |
| Soggetto topico |
Case-based reasoning
Expert systems (Computer science) Deep learning (Machine learning) |
| ISBN | 3-031-14923-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Invited Talks -- Seeing Through Black Boxes with Human Vision: Deep Learning and Explainable AI in Medical Image Applications -- Case-Based Reasoning for Clinical Decisions That Are Computer-Aided, Not Automated -- Towards More Cognitively Appealing Paradigms in Case-Based Reasoning -- Contents -- Explainability in CBR -- Using Case-Based Reasoning for Capturing Expert Knowledge on Explanation Methods -- 1 Introduction -- 2 Background -- 3 Case-Based Elicitation -- 3.1 Case Structure -- 3.2 Case Base Acquisition -- 4 CBR Process -- 5 Evaluation and Discussion -- 6 Conclusions -- References -- A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations -- 1 Introduction -- 2 Related Work -- 2.1 What Are Good Counterfactual Explanations? -- 2.2 Perturbation-Based Approaches -- 2.3 Instance-Based Approaches -- 2.4 Instance-Based Shortcomings -- 3 Good Counterfactuals in Multi-class Domains -- 3.1 Reusing the kNN Explanation Cases -- 3.2 Validating Candidate Counterfactuals -- 3.3 Discussion -- 4 Evaluation -- 4.1 Methodology -- 4.2 Results -- 5 Conclusions -- References -- How Close Is Too Close? The Role of Feature Attributions in Discovering Counterfactual Explanations -- 1 Introduction -- 2 Related Work -- 3 DisCERN -- 3.1 Nearest-Unlike Neighbour -- 3.2 Feature Ordering by Feature Attribution -- 3.3 Substitution-Based Adaptation -- 3.4 Integrated Gradients for DisCERN -- 3.5 Bringing the NUN Closer -- 4 Evaluation -- 4.1 Datasets -- 4.2 Experiment Setup -- 4.3 Performance Measures for Counterfactual Explanations -- 5 Results -- 5.1 A Comparison of Feature Attribution Techniques -- 5.2 A Comparison of Counterfactual Discovery Algorithms -- 5.3 Impact of Bringing NUN Closer -- 6 Conclusions -- References -- Algorithmic Bias and Fairness in Case-Based Reasoning.
1 Introduction -- 2 Related Research -- 2.1 Bias in ML -- 2.2 Bias in CBR -- 2.3 Metric Learning -- 3 FairRet: Eliminating Bias with Metric Learning -- 3.1 Bias and The Similarity Knowledge Container -- 3.2 A Metric Learning Approach -- 3.3 Multi-objective Particle Swarm Optimization -- 4 Results -- 4.1 Dealing with Underestimation Bias -- 4.2 Outcome Distortion -- 4.3 Retrieval Overlap -- 5 Conclusions -- References -- "Better" Counterfactuals, Ones People Can Understand: Psychologically-Plausible Case-Based Counterfactuals Using Categorical Features for Explainable AI (XAI) -- 1 Introduction -- 2 Background: Computation and Psychology of Counterfactuals -- 2.1 User Studies of Counterfactual XAI: Mixed Results -- 3 Study 1: Plotting Counterfactuals that have Categoricals -- 3.1 Results and Discussion -- 4 Transforming Case-Based Counterfactuals, Categorically -- 4.1 Case-Based Counterfactual Methods: CB1-CF and CB2-CF -- 4.2 Counterfactuals with Categorical Transforms #1: Global Binning -- 4.3 Counterfactuals with Categorical Transforms #2: Local Direction -- 5 Study 2: Evaluating CAT-CF Methods -- 5.1 Method: Data and Procedure -- 5.2 Results and Discussion: Counterfactual Distance -- 6 Conclusions -- References -- Representation and Similarity -- Extracting Case Indices from Convolutional Neural Networks: A Comparative Study -- 1 Introduction -- 2 Potential Feature Extraction Points in cnns -- 3 Related Work -- 4 Three Structure-Based Feature Extraction Methods -- 4.1 Post-convolution Feature Extraction -- 4.2 Post-dense Feature Extraction -- 4.3 Multi-net Feature Extraction -- 5 Evaluation -- 5.1 Hypotheses -- 5.2 Test Domain and Test Set Selection -- 5.3 Testbed System -- 5.4 Accuracy Testing and Informal Upper Bound -- 6 Results and Discussion -- 6.1 Comparative Performance -- 6.2 Discussion -- 7 Ramifications for Interpretability. 8 Conclusions and Future Work -- References -- Exploring the Effect of Recipe Representation on Critique-Based Conversational Recommendation -- 1 Introduction -- 2 Background -- 2.1 Diversity in Recommender Systems -- 2.2 Critique-Based Conversational Recommender Systems -- 2.3 Diversity in Recipe Recommenders -- 3 DiversityBite Framework: Recommend, Review, Revise -- 3.1 Adaptive Diversity Goal Approach -- 4 Evaluation -- 4.1 Case Base -- 4.2 Implementation: DGF, AGD, and Diversity Scoring -- 4.3 Simulation Study: Incorporating Diversity in Critique -- 4.4 User Study: Comparing Different Recipe Representations -- 5 Conclusion -- References -- Explaining CBR Systems Through Retrieval and Similarity Measure Visualizations: A Case Study -- 1 Introduction -- 2 Related Work -- 3 SupportPrim CBR System -- 3.1 Data -- 3.2 Case Representation and Similarity Modeling -- 3.3 Case Base and Similarity Population -- 4 Explanatory Case Base Visualizations -- 4.1 Accessing the CBR System's Model -- 4.2 Visualization of Retrievals -- 4.3 Visualization of the Similarity Scores for Individual Case Comparisons -- 5 Experiments -- 6 Discussion -- 7 Conclusion -- References -- Adapting Semantic Similarity Methods for Case-Based Reasoning in the Cloud -- 1 Introduction -- 2 Related Work -- 2.1 Clood CBR -- 2.2 Ontologies in CBR -- 2.3 Retrieval with Word Embedding -- 2.4 Serverless Function Benefits and Limitations -- 3 Semantic Similarity Metrics in a Microservices Architecture -- 3.1 Clood Similarity Functions Overview -- 3.2 Similarity Table -- 3.3 Word Embedding Based Similarity -- 3.4 Ontology-Based Similarity Measure -- 4 Implementation of Semantic Similarity Measures on Clood Framework -- 4.1 Word Embedding Similarity on Clood -- 4.2 Ontology-Based Similarity on Clood -- 5 Evaluation of Resource Impact -- 5.1 Experiment Setup -- 5.2 Result and Discussion. 6 Conclusion -- References -- Adaptation and Analogical Reasoning -- Case Adaptation with Neural Networks: Capabilities and Limitations -- 1 Introduction -- 2 Background -- 3 NN-CDH for both Classification and Regression -- 3.1 General Model of Case Adaptation -- 3.2 1-Hot/1-Cold Nominal Difference -- 3.3 Neural Network Structure of NN-CDH -- 3.4 Training and Adaptation Procedure -- 4 Evaluation -- 4.1 Systems Being Compared -- 4.2 Assembling Case Pairs for Training -- 4.3 Data Sets -- 4.4 Artificial Data Sets -- 5 Conclusion -- References -- A Deep Learning Approach to Solving Morphological Analogies -- 1 Introduction -- 2 The Problem of Morphological Analogy -- 3 Proposed Approach -- 3.1 Classification, Retrieval and Embedding Models -- 3.2 Training and Evaluation -- 4 Experiments -- 4.1 Data -- 4.2 Refining the Training Procedure -- 4.3 Performance Comparison with State of the Art Methods -- 4.4 Distance of the Expected Result -- 4.5 Case Analysis: Navajo and Georgian -- 5 Conclusion and Perspectives -- References -- Theoretical and Experimental Study of a Complexity Measure for Analogical Transfer -- 1 Introduction -- 2 Reminder on Complexity-Based Analogy -- 2.1 Notations -- 2.2 Ordinal Analogical Principle: Complexity Definition -- 2.3 Ordinal Analogical Inference Algorithm -- 3 Theoretical Property of the Complexity Measure: Upper Bound -- 3.1 General Case -- 3.2 Binary Classification Case -- 4 Algorithmic Optimisation -- 4.1 Principle -- 4.2 Proposed Optimized Algorithm -- 5 Experimental Study -- 5.1 Computational Cost -- 5.2 Correlation Between Case Base Complexity and Performance -- 5.3 Correlation Between Complexity and Task Difficulty -- 6 Conclusion and Future Works -- References -- Graphs and Optimisation -- Case-Based Learning and Reasoning Using Layered Boundary Multigraphs -- 1 Introduction -- 2 Background and Related Work. 3 Boundary Graphs and Labeled Boundary Multigraphs -- 3.1 Boundary Graphs -- 3.2 Labeled Boundary Multigraphs -- 3.3 Discussion -- 4 Empirical Evaluation -- 4.1 Experimental Set-Up -- 4.2 Classical Benchmark Data Sets -- 4.3 Scaling Analysis -- 5 Conclusion -- References -- Particle Swarm Optimization in Small Case Bases for Software Effort Estimation -- 1 Introduction -- 2 Related Work -- 3 Software Effort Estimation of User Stories -- 4 CBR Approach -- 4.1 Case Representation -- 4.2 Similarity -- 4.3 Adaptation -- 4.4 Weight Optimization with PSO -- 5 Experiments -- 5.1 Experimental Data -- 5.2 Experiment 1 -- 5.3 Experiment 2 -- 5.4 Discussion of Results -- 6 Conclusion -- References -- MicroCBR: Case-Based Reasoning on Spatio-temporal Fault Knowledge Graph for Microservices Troubleshooting -- 1 Introduction -- 2 Related Work -- 3 Background and Motivation -- 3.1 Background with Basic Concepts -- 3.2 Motivation -- 4 Troubleshooting Framework -- 4.1 Framework Overview -- 4.2 Spatio-Temporal Fault Knowledge Graph -- 4.3 Fingerprinting the Fault -- 4.4 Case-Based Reasoning -- 5 Evaluation -- 5.1 Evaluation Setup -- 5.2 Q1. Comparative Experiments -- 5.3 Q2. Ablation Experiment -- 5.4 Q3. Efficiency Experiments -- 5.5 Q4. Case Studies and Learned Lessons -- 6 Conclusion -- References -- .26em plus .1em minus .1emGPU-Based Graph Matching for Accelerating Similarity Assessment in Process-Oriented Case-Based Reasoning -- 1 Introduction -- 2 Foundations and Related Work -- 2.1 Semantic Workflow Graph Representation -- 2.2 State-Space Search by Using A* -- 2.3 Related Work -- 3 AMonG: A*-Based Graph Matching on Graphic Processing Units -- 3.1 Overview and Components -- 3.2 Parallel Graph Matching -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Experimental Results -- 4.3 Discussion and Further Considerations -- 5 Conclusion and Future Work. References. |
| Record Nr. | UNISA-996485668603316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Case-Based Reasoning Research and Development [[electronic resource] ] : 20th International Conference, ICCBR 2012, Lyon, France, September 3-6, 2012, Proceedings / / edited by Belén Díaz Agudo, Ian Watson
| Case-Based Reasoning Research and Development [[electronic resource] ] : 20th International Conference, ICCBR 2012, Lyon, France, September 3-6, 2012, Proceedings / / edited by Belén Díaz Agudo, Ian Watson |
| Edizione | [1st ed. 2012.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 |
| Descrizione fisica | 1 online resource (XI, 416 p. 132 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Case-based reasoning Data mining Application software User interfaces (Computer systems) Artificial Intelligence Information Storage and Retrieval Data Mining and Knowledge Discovery Information Systems Applications (incl. Internet) User Interfaces and Human Computer Interaction Computer Appl. in Administrative Data Processing |
| Soggetto genere / forma | Conference proceedings. |
| ISBN | 3-642-32986-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996465761503316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2012 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Case-based reasoning research and development : 8th International Conference on Case-Based Reasoning, ICCBR 2009, Seattle, WA, USA, July 20-23, 2009 : proceedings / / Lorraine McGinty, David C. Wilson (eds.)
| Case-based reasoning research and development : 8th International Conference on Case-Based Reasoning, ICCBR 2009, Seattle, WA, USA, July 20-23, 2009 : proceedings / / Lorraine McGinty, David C. Wilson (eds.) |
| Edizione | [1st ed. 2009.] |
| Pubbl/distr/stampa | Berlin, Germany : , : Springer, , [2009] |
| Descrizione fisica | 1 online resource (536 p.) |
| Disciplina | 006.333 |
| Collana |
Lecture notes in computer science
Lecture notes in artificial intelligence |
| Soggetto topico |
Artificial intelligence
Case-based reasoning Expert systems (Computer science) |
| ISBN |
1-282-29797-X
9786612297977 3-642-02998-1 |
| Classificazione |
DAT 706f
SS 4800 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Talks -- We’re Wiser Together -- Black Swans, Gray Cygnets and Other Rare Birds -- Theoretical/Methodological Research Papers -- Case Retrieval Reuse Net (CR2N): An Architecture for Reuse of Textual Solutions -- Case-Based Reasoning in Transfer Learning -- Toward Modeling and Teaching Legal Case-Based Adaptation with Expert Examples -- Opportunistic Adaptation Knowledge Discovery -- Improving Reinforcement Learning by Using Case Based Heuristics -- Dimensions of Case-Based Reasoner Quality Management -- Belief Merging-Based Case Combination -- Maintenance by a Committee of Experts: The MACE Approach to Case-Base Maintenance -- The Good, the Bad and the Incorrectly Classified: Profiling Cases for Case-Base Editing -- An Active Approach to Automatic Case Generation -- Four Heads Are Better than One: Combining Suggestions for Case Adaptation -- Adaptation versus Retrieval Trade-Off Revisited: An Analysis of Boundary Conditions -- Boosting CBR Agents with Genetic Algorithms -- Using Meta-reasoning to Improve the Performance of Case-Based Planning -- Multi-level Abstractions and Multi-dimensional Retrieval of Cases with Time Series Features -- On Similarity Measures Based on a Refinement Lattice -- An Overview of the Deterministic Dynamic Associative Memory (DDAM) Model for Case Representation and Retrieval -- Robust Measures of Complexity in TCBR -- S-Learning: A Model-Free, Case-Based Algorithm for Robot Learning and Control -- Quality Enhancement Based on Reinforcement Learning and Feature Weighting for a Critiquing-Based Recommender -- Abstraction in Knowledge-Rich Models for Case-Based Planning -- A Scalable Noise Reduction Technique for Large Case-Based Systems -- Conceptual Neighborhoods for Retrieval in Case-Based Reasoning -- CBR Supports Decision Analysis with Uncertainty -- Constraint-Based Case-Based Planning Using Weighted MAX-SAT -- Applied Research Papers -- A Value Supplementation Method for Case Bases with Incomplete Information -- Efficiently Implementing Episodic Memory -- Integration of a Methodology for Cluster-Based Retrieval in jColibri -- Case-Based Collective Inference for Maritime Object Classification -- Case-Based Reasoning for Situation-Aware Ambient Intelligence: A Hospital Ward Evaluation Study -- Spatial Event Prediction by Combining Value Function Approximation and Case-Based Reasoning -- Case-Based Support for Forestry Decisions: How to See the Wood from the Trees -- A Case-Based Perspective on Social Web Search -- Determining Root Causes of Drilling Problems by Combining Cases and General Knowledge. |
| Record Nr. | UNISA-996465847203316 |
| Berlin, Germany : , : Springer, , [2009] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Case-based reasoning technology : from foundations to applications / / Mario Lenz [and four others] editors
| Case-based reasoning technology : from foundations to applications / / Mario Lenz [and four others] editors |
| Edizione | [1st ed. 1998.] |
| Pubbl/distr/stampa | Berlin ; ; Heidelberg : , : Springer, , [1998] |
| Descrizione fisica | 1 online resource (XIV, 405 p. 82 illus., 11 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico | Case-based reasoning |
| ISBN | 3-540-69351-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Extending some Concepts of CBR — Foundations of Case Retrieval Nets -- Diagnosis and Decision Support -- Intelligent Sales Support with CBR -- Textual CBR -- Using Configuration Techniques for Adaptation -- CBR Applied to Planning -- CBR for Design -- CBR for Experimental Software Engineering -- CBR for Tutoring and Help Systems -- CBR in Medicine -- Methodology for Building CBR Applications -- Related Areas. |
| Record Nr. | UNINA-9910143452403321 |
| Berlin ; ; Heidelberg : , : Springer, , [1998] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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