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Capire i sistemi esperti / Louis E. Frenzel
| Capire i sistemi esperti / Louis E. Frenzel |
| Autore | Frenzel, Louis E. |
| Pubbl/distr/stampa | Milano : Tecniche Nuove, ©1988 |
| Descrizione fisica | 199 p. : ill. ; 24 cm |
| Disciplina | 006.33 |
| Collana | Capire l'elettronica e l'informatica |
| Soggetto non controllato | Sistema esperto |
| ISBN | 88-7081-422-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | ita |
| Record Nr. | UNINA-990000509650403321 |
Frenzel, Louis E.
|
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| Milano : Tecniche Nuove, ©1988 | ||
| 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. | UNINA-9910502645803321 |
|
Sánchez-Ruiz Antonio A.
|
||
| Cham, Switzerland : , : Springer International Publishing, , [2021] | ||
| 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.
|
||
| Cham, Switzerland : , : Springer International Publishing, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Case-Based Reasoning Research and Development [[electronic resource] ] : 7th International Conference on Case-Based Reasoning, ICCBR 2007 Belfast Northern Ireland, UK, August 13-16, 2007 Proceedings / / edited by Rosina O. Weber, Michael M. Richter
| Case-Based Reasoning Research and Development [[electronic resource] ] : 7th International Conference on Case-Based Reasoning, ICCBR 2007 Belfast Northern Ireland, UK, August 13-16, 2007 Proceedings / / edited by Rosina O. Weber, Michael M. Richter |
| Edizione | [1st ed. 2007.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2007 |
| Descrizione fisica | 1 online resource (XIII, 538 p.) |
| Disciplina | 006.33 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Mathematical logic Information technology Business—Data processing Artificial Intelligence Mathematical Logic and Formal Languages IT in Business |
| ISBN | 3-540-74141-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Cases in Robotic Soccer -- A Case-Based Framework for Collaborative Semantic Search in Knowledge Sifter -- Usages of Generalization in Case-Based Reasoning -- Research Papers -- Team Playing Behavior in Robot Soccer: A Case-Based Reasoning Approach -- Acquiring Word Similarities with Higher Order Association Mining -- Label Ranking in Case-Based Reasoning -- When Similar Problems Don’t Have Similar Solutions -- Mixed-Initiative Relaxation of Constraints in Critiquing Dialogues -- A Methodology for Analyzing Case Retrieval from a Clustered Case Memory -- Using Cases Utility for Heuristic Planning Improvement -- Case-Based Reasoning Adaptation for High Dimensional Solution Space -- Case-Based Planning and Execution for Real-Time Strategy Games -- Case Authoring: From Textual Reports to Knowledge-Rich Cases -- Case Provenance: The Value of Remembering Case Sources -- Mining Large-Scale Knowledge Sources for Case Adaptation Knowledge -- Representation and Structure-Based Similarity Assessment for Agile Workflows -- Application of the Revision Theory to Adaptation in Case-Based Reasoning: The Conservative Adaptation -- Methodological Assistance for Integrating Data Quality Evaluations into Case-Based Reasoning Systems -- Case-Based Anomaly Detection -- Case-Based Reasoning in Robot Indoor Navigation -- Case-Based Group Recommendation: Compromising for Success -- Catching the Drift: Using Feature-Free Case-Based Reasoning for Spam Filtering -- Enhancing Case-Based, Collaborative Web Search -- An Analysis of Case-Based Value Function Approximation by Approximating State Transition Graphs -- From Anomaly Reports to Cases -- Assessing Classification Accuracy in the Revision Stage of a CBR Spam Filtering System -- Application Papers -- Intelligent Guidance and Suggestions Using Case-Based Planning -- Case-Based Reasoning for Invoice Analysis and Recognition -- Watershed Segmentation Via Case-Based Reasoning -- A Case-Based Song Scheduler for Group Customised Radio -- Helping Software Engineers Reusing UML Class Diagrams -- Failure Analysis for Domain Knowledge Acquisition in a Knowledge-Intensive CBR System -- Classify and Diagnose Individual Stress Using Calibration and Fuzzy Case-Based Reasoning -- Prototypical Cases for Knowledge Maintenance in Biomedical CBR -- Case-Based Support for Library Reference Services -- Knowledge Extraction and Summarization for an Application of Textual Case-Based Interpretation. |
| Record Nr. | UNISA-996465894403316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Case-Based Reasoning Research and Development : 7th International Conference on Case-Based Reasoning, ICCBR 2007 Belfast Northern Ireland, UK, August 13-16, 2007 Proceedings / / edited by Rosina O. Weber, Michael M. Richter
| Case-Based Reasoning Research and Development : 7th International Conference on Case-Based Reasoning, ICCBR 2007 Belfast Northern Ireland, UK, August 13-16, 2007 Proceedings / / edited by Rosina O. Weber, Michael M. Richter |
| Edizione | [1st ed. 2007.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2007 |
| Descrizione fisica | 1 online resource (XIII, 538 p.) |
| Disciplina | 006.33 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Logic, Symbolic and mathematical Information technology Business—Data processing Artificial Intelligence Mathematical Logic and Formal Languages IT in Business |
| ISBN | 3-540-74141-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Cases in Robotic Soccer -- A Case-Based Framework for Collaborative Semantic Search in Knowledge Sifter -- Usages of Generalization in Case-Based Reasoning -- Research Papers -- Team Playing Behavior in Robot Soccer: A Case-Based Reasoning Approach -- Acquiring Word Similarities with Higher Order Association Mining -- Label Ranking in Case-Based Reasoning -- When Similar Problems Don’t Have Similar Solutions -- Mixed-Initiative Relaxation of Constraints in Critiquing Dialogues -- A Methodology for Analyzing Case Retrieval from a Clustered Case Memory -- Using Cases Utility for Heuristic Planning Improvement -- Case-Based Reasoning Adaptation for High Dimensional Solution Space -- Case-Based Planning and Execution for Real-Time Strategy Games -- Case Authoring: From Textual Reports to Knowledge-Rich Cases -- Case Provenance: The Value of Remembering Case Sources -- Mining Large-Scale Knowledge Sources for Case Adaptation Knowledge -- Representation and Structure-Based Similarity Assessment for Agile Workflows -- Application of the Revision Theory to Adaptation in Case-Based Reasoning: The Conservative Adaptation -- Methodological Assistance for Integrating Data Quality Evaluations into Case-Based Reasoning Systems -- Case-Based Anomaly Detection -- Case-Based Reasoning in Robot Indoor Navigation -- Case-Based Group Recommendation: Compromising for Success -- Catching the Drift: Using Feature-Free Case-Based Reasoning for Spam Filtering -- Enhancing Case-Based, Collaborative Web Search -- An Analysis of Case-Based Value Function Approximation by Approximating State Transition Graphs -- From Anomaly Reports to Cases -- Assessing Classification Accuracy in the Revision Stage of a CBR Spam Filtering System -- Application Papers -- Intelligent Guidance and Suggestions Using Case-Based Planning -- Case-Based Reasoning for Invoice Analysis and Recognition -- Watershed Segmentation Via Case-Based Reasoning -- A Case-Based Song Scheduler for Group Customised Radio -- Helping Software Engineers Reusing UML Class Diagrams -- Failure Analysis for Domain Knowledge Acquisition in a Knowledge-Intensive CBR System -- Classify and Diagnose Individual Stress Using Calibration and Fuzzy Case-Based Reasoning -- Prototypical Cases for Knowledge Maintenance in Biomedical CBR -- Case-Based Support for Library Reference Services -- Knowledge Extraction and Summarization for an Application of Textual Case-Based Interpretation. |
| Record Nr. | UNINA-9910768173203321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2007 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Case-based reasoning technology : from foundations to applications / Mario Lenza ... <et al.>
| Case-based reasoning technology : from foundations to applications / Mario Lenza ... <et al.> |
| Autore | LENZA, Mario |
| Pubbl/distr/stampa | Berlin : Springer, c1998 |
| Descrizione fisica | XVIII, 405 p. ; 24 cm |
| Disciplina | 006.33 |
| Collana | Lecture notes in computer science, Lecture notes in artificial intelligence |
| Soggetto topico |
Sistemi esperti
Sistemi esperti - Impiego nelle aziende |
| ISBN | 3-540-64572-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-990000465640203316 |
|
LENZA, Mario
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| Berlin : Springer, c1998 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Citizen Privacy Framework : Case of a Fuzzy-based Recommender System for Political Participation / / by Aigul Kaskina
| Citizen Privacy Framework : Case of a Fuzzy-based Recommender System for Political Participation / / by Aigul Kaskina |
| Autore | Kaskina Aigul |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (121 pages) |
| Disciplina |
005.8
006.33 |
| Collana | Fuzzy Management Methods |
| Soggetto topico |
Business information services
Application software Social sciences - Data processing Data protection Business Information Systems Computer and Information Systems Applications Computer Application in Social and Behavioral Sciences Data and Information Security |
| ISBN |
9783031060212
9783031060205 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Introduction -- Chapter 2. Insights into Privacy Research -- Chapter 3. Citizen Privacy Profile Framework -- Chapter 4. Fuzzy-based Privacy Settings Recommender System -- Chapter 5. Conclusions. |
| Record Nr. | UNINA-9910595055003321 |
|
Kaskina Aigul
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Cognitive computing and big data analytics / / Judith Hurwitz, Marcia Kaufman, Adrian Bowles
| Cognitive computing and big data analytics / / Judith Hurwitz, Marcia Kaufman, Adrian Bowles |
| Autore | Hurwitz Judith S. |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Indianapolis, Indiana : , : Wiley, , 2015 |
| Descrizione fisica | 1 online resource (256 p.) |
| Disciplina | 006.33 |
| Soggetto topico |
Expert systems (Computer science)
Big data Artificial intelligence |
| ISBN |
1-118-89678-5
1-119-18364-2 1-118-89663-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The foundation of cognitive computing -- Design principles for cognitive systems -- Natural language processing in support of a cognitive system -- The relationship between big data and cognitive computing -- Representing knowledge in taxonomies and ontologies -- Applying advanced analytics to cognitive computing -- The role of cloud and distributed computing in cognitive computing -- The business implications of cognitive computing -- IBM's Watson as a cognitive system -- The process of building a cognitive application -- Building a cognitive healthcare application -- Smarter cities : cognitive computing in government -- Emerging cognitive computing areas -- Future applications for cognitive computing. |
| Record Nr. | UNINA-9910208952003321 |
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Hurwitz Judith S.
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| Indianapolis, Indiana : , : Wiley, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Cognitive computing and big data analytics / Judith Hurwitz, Marcia Kaufman, Adrian Bowles
| Cognitive computing and big data analytics / Judith Hurwitz, Marcia Kaufman, Adrian Bowles |
| Autore | Hurwitz, Judith |
| Descrizione fisica | xxi, 266 p. : ill. ; 24 cm |
| Disciplina | 006.33 |
| Altri autori (Persone) | Kaufman, Marciaauthor |
| Soggetto topico |
Artificial intelligence
Cognitive science Human-computer interaction |
| ISBN | 9781118896624 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | The foundation of cognitive computing -- Design principles for cognitive systems -- Natural language processing in support of a cognitive system -- The relationship between big data and cognitive computing -- Representing knowledge in taxonomies and ontologies -- Applying advanced analytics to cognitive computing -- The role of cloud and distributed computing in cognitive computing -- The business implications of cognitive computing -- IBM's Watson as a cognitive system -- The process of building a cognitive application -- Building a cognitive healthcare application -- Smarter cities : cognitive computing in government -- Emerging cognitive computing areas -- Future applications for cognitive computing |
| Record Nr. | UNISALENTO-991004035359707536 |
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Hurwitz, Judith
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| Materiale a stampa | ||
| Lo trovi qui: Univ. del Salento | ||
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Computational collective intelligence : 13th international conference, ICCCI 2021, Rhodes, Greece, September 29-October 1, 2021, proceedings / / edited by Ngoc Thanh Nguyen [and three others]
| Computational collective intelligence : 13th international conference, ICCCI 2021, Rhodes, Greece, September 29-October 1, 2021, proceedings / / edited by Ngoc Thanh Nguyen [and three others] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (817 pages) |
| Disciplina | 006.33 |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Expert systems (Computer science)
Intelligent agents (Computer software) |
| ISBN | 3-030-88081-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464488803316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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