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Foundations of Intelligent Systems [[electronic resource] ] : 18th International Symposium, ISMIS 2009, Prague, Czech Republic, September 14-17, 2009, Proceedings / / edited by Jan Rauch, Zbigniew W. Ras, Petr Berka, Tapio Elomaa
| Foundations of Intelligent Systems [[electronic resource] ] : 18th International Symposium, ISMIS 2009, Prague, Czech Republic, September 14-17, 2009, Proceedings / / edited by Jan Rauch, Zbigniew W. Ras, Petr Berka, Tapio Elomaa |
| Edizione | [1st ed. 2009.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009 |
| Descrizione fisica | 1 online resource (XVI, 624 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Information storage and retrieval Application software Database management User interfaces (Computer systems) Artificial Intelligence Data Mining and Knowledge Discovery Information Storage and Retrieval Information Systems Applications (incl. Internet) Database Management User Interfaces and Human Computer Interaction |
| ISBN | 3-642-04125-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Invited Papers -- Randomization Methods for Assessing the Significance of Data Mining Results -- Dealing with Music in Intelligent Ways -- Intelligent Systems: From R.U.R. to ISMIS 2009 and beyond -- The Art of Management and the Technology of Knowledge-Based Systems -- Knowledge Discovery and Data Mining -- Frequent Itemset Mining in Multirelational Databases -- A Multiple Scanning Strategy for Entropy Based Discretization -- Fast Subgroup Discovery for Continuous Target Concepts -- Discovering Emerging Graph Patterns from Chemicals -- Visualization of Trends Using RadViz -- Action Rules Discovery Based on Tree Classifiers and Meta-actions -- Action Rules and the GUHA Method: Preliminary Considerations and Results -- Semantic Analytical Reports: A Framework for Post-processing Data Mining Results -- Applications of Intelligent Systems in Medicine -- Medical Decision Making through Fuzzy Computational Intelligent Approaches -- Fuzzy Cognitive Map Based Approach for Assessing Pulmonary Infections -- A Knowledge-Based Framework for Information Extraction from Clinical Practice Guidelines -- RaJoLink: A Method for Finding Seeds of Future Discoveries in Nowadays Literature -- Logical and Theoretical Aspects of Intelligent Systems -- Automatic Generation of P2P Mappings between Sources Schemas -- An OWL Ontology for Fuzzy OWL 2 -- Fuzzy Clustering for Categorical Spaces -- Reasoning about Relations with Dependent Types: Application to Context-Aware Applications -- Quasi-Classical Model Semantics for Logic Programs – A Paraconsistent Approach -- Prime Implicates and Reduced Implicate Tries -- Logic for Reasoning about Components of Persuasive Actions -- A Hybrid Method of Indexing Multiple-Inheritance Hierarchies -- Text Mining -- Theme Extraction from Chinese Web Documents Based on Page Segmentation and Entropy -- Topic-Based Hard Clustering of Documents Using Generative Models -- Boosting a Semantic Search Engine by Named Entities -- Detecting Temporal Trends of Technical Phrases by Using Importance Indices and Linear Regression -- Applications of Intelligent Systems in Music -- Detecting Emotions in Classical Music from MIDI Files -- Mining Musical Patterns: Identification of Transposed Motives -- Musical Instruments in Random Forest -- Application of Analysis of Variance to Assessment of Influence of Sound Feature Groups on Discrimination between Musical Instruments -- Information Processing -- Alternative Formulas for Rating Prediction Using Collaborative Filtering -- On Three Classes of Division Queries Involving Ordinal Preferences -- Analyses of Knowledge Creation Processes Based on Different Types of Monitored Data -- Intelligent Information Processing in Semantically Enriched Web -- Agents -- Modeling Ant Activity by Means of Structured HMMs -- Modern Approach for Building of Multi-Agent Systems -- Relational Sequence Clustering for Aggregating Similar Agents -- FutureTrust Algorithm in Specific Factors on Mobile Agents -- Machine Learning -- Ensembles of Abstaining Classifiers Based on Rule Sets -- Elicitation of Sugeno Integrals: A Version Space Learning Perspective -- Efficient MAP Inference for Statistical Relational Models through Hybrid Metaheuristics -- Combining Time and Space Similarity for Small Size Learning under Concept Drift -- Similarity and Kernel Matrix Evaluation Based on Spatial Autocorrelation Analysis -- Applications of Intelligent Systems -- Job Offer Management: How Improve the Ranking of Candidates -- Discovering Structured Event Logs from Unstructured Audit Trails for Workflow Mining -- GIS-FLSolution: A Spatial Analysis Platform for Static and Transportation Facility Location Allocation Problem -- A CBR System for Knowing the Relationship between Flexibility and Operations Strategy -- Semantic-Based Top-k Retrieval for Competence Management -- A New Strategy Based on GRASP to Solve a Macro Mine Planning -- Food Wholesales Prediction: What Is Your Baseline? -- Complex Data -- A Distributed Immunization Strategy Based on Autonomy-Oriented Computing -- Discovering Relevant Cross-Graph Cliques in Dynamic Networks -- Statistical Characterization of a Computer Grid -- On Social Networks Reduction -- Networks Consolidation through Soft Computing -- Lacking Labels in the Stream: Classifying Evolving Stream Data with Few Labels -- Novelty Detection from Evolving Complex Data Streams with Time Windows -- General AI -- On Computational Creativity, ‘Inventing’ Theorem Proofs -- Revisiting Constraint Models for Planning Problems -- Uncertainty -- Interval-Valued Fuzzy Formal Concept Analysis -- Application of Meta Sets to Character Recognition -- A General Framework for Revising Belief Bases Using Qualitative Jeffrey’s Rule. |
| Record Nr. | UNISA-996465298403316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2009 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Principles of data mining and knowledge discovery : Third European Conference, PKDD '99, Prague, Czech Republic, September 15-18, 1999 : proceedings / / Jan M. Żytkow, Jan Rauch (editors)
| Principles of data mining and knowledge discovery : Third European Conference, PKDD '99, Prague, Czech Republic, September 15-18, 1999 : proceedings / / Jan M. Żytkow, Jan Rauch (editors) |
| Edizione | [1st ed. 1999.] |
| Pubbl/distr/stampa | Berlin, Germany : , : Springer, , [1999] |
| Descrizione fisica | 1 online resource (XIV, 593 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Database searching |
| ISBN | 3-540-48247-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Session 1A - Time Series -- Scaling up Dynamic Time Warping to Massive Datasets -- The Haar Wavelet Transform in the Time Series Similarity Paradigm -- Rule Discovery in Large Time-Series Medical Databases -- Session 1B - Applications -- Simultaneous Prediction of Multiple Chemical Parameters of River Water Quality with TILDE -- Applying Data Mining Techniques to Wafer Manufacturing -- An Application of Data Mining to the Problem of the University Students’ Dropout Using Markov Chains -- Session 2A - Taxonomies and Partitions -- Discovering and Visualizing Attribute Associations Using Bayesian Networks and Their Use in KDD -- Taxonomy Formation by Approximate Equivalence Relations, Revisited -- On the Use of Self-Organizing Maps for Clustering and Visualization -- Speeding Up the Search for Optimal Partitions -- Session 2B - Logic Methods -- Experiments in Meta-level Learning with ILP -- Boolean Reasoning Scheme with Some Applications in Data Mining -- On the Correspondence between Classes of Implicational and Equivalence Quantifiers -- Querying Inductive Databases via Logic-Based User-Defined Aggregates -- Session 3A - Distributed and Multirelational Databases -- Peculiarity Oriented Multi-database Mining -- Knowledge Discovery in Medical Multi-databases: A Rough Set Approach -- Automated Discovery of Rules and Exceptions from Distributed Databases Using Aggregates -- Session 3B - Text Mining and Feature Selection -- Text Mining via Information Extraction -- TopCat: Data Mining for Topic Identification in a Text Corpus -- Selection and Statistical Validation of Features and Prototypes -- Session 4A - Rules and Induction -- Taming Large Rule Models in Rough Set Approaches -- Optimizing Disjunctive Association Rules -- Contribution of Boosting in Wrapper Models -- Experiments on a Representation-Independent “Top-Down and Prune” Induction Scheme -- Session 5A - Interesting and Unusual -- Heuristic Measures of Interestingness -- Enhancing Rule Interestingness for Neuro-fuzzy Systems -- Unsupervised Profiling for Identifying Superimposed Fraud -- OPTICS-OF: Identifying Local Outliers -- Posters -- Selective Propositionalization for Relational Learning -- Circle Graphs: New Visualization Tools for Text-Mining -- On the Consistency of Information Filters for Lazy Learning Algorithms -- Using Genetic Algorithms to Evolve a Rule Hierarchy -- Mining Temporal Features in Association Rules -- The Improvement of Response Modeling: Combining Rule-Induction and Case-Based Reasoning -- Analyzing an Email Collection Using Formal Concept Analysis -- Business Focused Evaluation Methods: A Case Study -- Combining Data and Knowledge by MaxEnt-Optimization of Probability Distributions -- Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation? -- Rough Dependencies as a Particular Case of Correlation: Application to the Calculation of Approximative Reducts -- A Fuzzy Beam-Search Rule Induction Algorithm -- An Innovative GA-Based Decision Tree Classifier in Large Scale Data Mining -- Extension to C-means Algorithm for the Use of Similarity Functions -- Predicting Chemical Carcinogenesis Using Structural Information Only -- LA – A Clustering Algorithm with an Automated Selection of Attributes, Which is Invariant to Functional Transformations of Coordinates -- Association Rule Selection in a Data Mining Environment -- Multi-relational Decision Tree Induction -- Learning of Simple Conceptual Graphs from Positive and Negative Examples -- An Evolutionary Algorithm Using Multivariate Discretization for Decision Rule Induction -- ZigZag, a New Clustering Algorithm to Analyze Categorical Variable Cross-Classification Tables -- Efficient Mining of High Confidence Association Rules without Support Thresholds -- A Logical Approach to Fuzzy Data Analysis -- AST: Support for Algorithm Selection with a CBR Approach -- Efficient Shared Near Neighbours Clustering of Large Metric Data Sets -- Discovery of “Interesting” Data Dependencies from a Workload of SQL Statements -- Learning from Highly Structured Data by Decomposition -- Combinatorial Approach for Data Binarization -- Extending Attribute-Oriented Induction as a Key-Preserving Data Mining Method -- Automated Discovery of Polynomials by Inductive Genetic Programming -- Diagnosing Acute Appendicitis with Very Simple Classification Rules -- Rule Induction in Cascade Model Based on Sum of Squares Decomposition -- Maintenance of Discovered Knowledge -- A Divisive Initialisation Method for Clustering Algorithms -- A Comparison of Model Selection Procedures for Predicting Turning Points in Financial Time Series -- Mining Lemma Disambiguation Rules from Czech Corpora -- Adding Temporal Semantics to Association Rules -- Studying the Behavior of Generalized Entropy in Induction Trees Using a M-of-N Concept -- Discovering Rules in Information Trees -- Mining Text Archives: Creating Readable Maps to Structure and Describe Document Collections -- Neuro-fuzzy Data Mining for Target Group Selection in Retail Banking -- Mining Possibilistic Set-Valued Rules by Generating Prime Disjunctions -- Towards Discovery of Information Granules -- Classification Algorithms Based on Linear Combinations of Features -- Managing Interesting Rules in Sequence Mining -- Support Vector Machines for Knowledge Discovery -- Regression by Feature Projections -- Generating Linguistic Fuzzy Rules for Pattern Classification with Genetic Algorithms -- Tutorials -- Data Mining for Robust Business Intelligence Solutions -- Query Languages for Knowledge Discovery in Databases -- The ESPRIT Project CreditMine and its Relevance for the Internet Market -- Logics and Statistics for Association Rules and Beyond -- Data Mining for the Web -- Relational Learning and Inductive Logic Programming Made Easy. |
| Record Nr. | UNISA-996465298003316 |
| Berlin, Germany : , : Springer, , [1999] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Principles of data mining and knowledge discovery : Third European Conference, PKDD '99, Prague, Czech Republic, September 15-18, 1999 : proceedings / / Jan M. Żytkow, Jan Rauch (editors)
| Principles of data mining and knowledge discovery : Third European Conference, PKDD '99, Prague, Czech Republic, September 15-18, 1999 : proceedings / / Jan M. Żytkow, Jan Rauch (editors) |
| Edizione | [1st ed. 1999.] |
| Pubbl/distr/stampa | Berlin, Germany : , : Springer, , [1999] |
| Descrizione fisica | 1 online resource (XIV, 593 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Database searching |
| ISBN | 3-540-48247-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Session 1A - Time Series -- Scaling up Dynamic Time Warping to Massive Datasets -- The Haar Wavelet Transform in the Time Series Similarity Paradigm -- Rule Discovery in Large Time-Series Medical Databases -- Session 1B - Applications -- Simultaneous Prediction of Multiple Chemical Parameters of River Water Quality with TILDE -- Applying Data Mining Techniques to Wafer Manufacturing -- An Application of Data Mining to the Problem of the University Students’ Dropout Using Markov Chains -- Session 2A - Taxonomies and Partitions -- Discovering and Visualizing Attribute Associations Using Bayesian Networks and Their Use in KDD -- Taxonomy Formation by Approximate Equivalence Relations, Revisited -- On the Use of Self-Organizing Maps for Clustering and Visualization -- Speeding Up the Search for Optimal Partitions -- Session 2B - Logic Methods -- Experiments in Meta-level Learning with ILP -- Boolean Reasoning Scheme with Some Applications in Data Mining -- On the Correspondence between Classes of Implicational and Equivalence Quantifiers -- Querying Inductive Databases via Logic-Based User-Defined Aggregates -- Session 3A - Distributed and Multirelational Databases -- Peculiarity Oriented Multi-database Mining -- Knowledge Discovery in Medical Multi-databases: A Rough Set Approach -- Automated Discovery of Rules and Exceptions from Distributed Databases Using Aggregates -- Session 3B - Text Mining and Feature Selection -- Text Mining via Information Extraction -- TopCat: Data Mining for Topic Identification in a Text Corpus -- Selection and Statistical Validation of Features and Prototypes -- Session 4A - Rules and Induction -- Taming Large Rule Models in Rough Set Approaches -- Optimizing Disjunctive Association Rules -- Contribution of Boosting in Wrapper Models -- Experiments on a Representation-Independent “Top-Down and Prune” Induction Scheme -- Session 5A - Interesting and Unusual -- Heuristic Measures of Interestingness -- Enhancing Rule Interestingness for Neuro-fuzzy Systems -- Unsupervised Profiling for Identifying Superimposed Fraud -- OPTICS-OF: Identifying Local Outliers -- Posters -- Selective Propositionalization for Relational Learning -- Circle Graphs: New Visualization Tools for Text-Mining -- On the Consistency of Information Filters for Lazy Learning Algorithms -- Using Genetic Algorithms to Evolve a Rule Hierarchy -- Mining Temporal Features in Association Rules -- The Improvement of Response Modeling: Combining Rule-Induction and Case-Based Reasoning -- Analyzing an Email Collection Using Formal Concept Analysis -- Business Focused Evaluation Methods: A Case Study -- Combining Data and Knowledge by MaxEnt-Optimization of Probability Distributions -- Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation? -- Rough Dependencies as a Particular Case of Correlation: Application to the Calculation of Approximative Reducts -- A Fuzzy Beam-Search Rule Induction Algorithm -- An Innovative GA-Based Decision Tree Classifier in Large Scale Data Mining -- Extension to C-means Algorithm for the Use of Similarity Functions -- Predicting Chemical Carcinogenesis Using Structural Information Only -- LA – A Clustering Algorithm with an Automated Selection of Attributes, Which is Invariant to Functional Transformations of Coordinates -- Association Rule Selection in a Data Mining Environment -- Multi-relational Decision Tree Induction -- Learning of Simple Conceptual Graphs from Positive and Negative Examples -- An Evolutionary Algorithm Using Multivariate Discretization for Decision Rule Induction -- ZigZag, a New Clustering Algorithm to Analyze Categorical Variable Cross-Classification Tables -- Efficient Mining of High Confidence Association Rules without Support Thresholds -- A Logical Approach to Fuzzy Data Analysis -- AST: Support for Algorithm Selection with a CBR Approach -- Efficient Shared Near Neighbours Clustering of Large Metric Data Sets -- Discovery of “Interesting” Data Dependencies from a Workload of SQL Statements -- Learning from Highly Structured Data by Decomposition -- Combinatorial Approach for Data Binarization -- Extending Attribute-Oriented Induction as a Key-Preserving Data Mining Method -- Automated Discovery of Polynomials by Inductive Genetic Programming -- Diagnosing Acute Appendicitis with Very Simple Classification Rules -- Rule Induction in Cascade Model Based on Sum of Squares Decomposition -- Maintenance of Discovered Knowledge -- A Divisive Initialisation Method for Clustering Algorithms -- A Comparison of Model Selection Procedures for Predicting Turning Points in Financial Time Series -- Mining Lemma Disambiguation Rules from Czech Corpora -- Adding Temporal Semantics to Association Rules -- Studying the Behavior of Generalized Entropy in Induction Trees Using a M-of-N Concept -- Discovering Rules in Information Trees -- Mining Text Archives: Creating Readable Maps to Structure and Describe Document Collections -- Neuro-fuzzy Data Mining for Target Group Selection in Retail Banking -- Mining Possibilistic Set-Valued Rules by Generating Prime Disjunctions -- Towards Discovery of Information Granules -- Classification Algorithms Based on Linear Combinations of Features -- Managing Interesting Rules in Sequence Mining -- Support Vector Machines for Knowledge Discovery -- Regression by Feature Projections -- Generating Linguistic Fuzzy Rules for Pattern Classification with Genetic Algorithms -- Tutorials -- Data Mining for Robust Business Intelligence Solutions -- Query Languages for Knowledge Discovery in Databases -- The ESPRIT Project CreditMine and its Relevance for the Internet Market -- Logics and Statistics for Association Rules and Beyond -- Data Mining for the Web -- Relational Learning and Inductive Logic Programming Made Easy. |
| Record Nr. | UNINA-9910767573603321 |
| Berlin, Germany : , : Springer, , [1999] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||