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Knowledge discovery and data mining : current issues and new applications : 4th Pacific-Asia Conference, PAKDD 2000, Kyoto, Japan, April 18-20, 2000 : proceedings / / Takao Terano, Huan Liu, Arbee L.P. Chen (eds.)
| Knowledge discovery and data mining : current issues and new applications : 4th Pacific-Asia Conference, PAKDD 2000, Kyoto, Japan, April 18-20, 2000 : proceedings / / Takao Terano, Huan Liu, Arbee L.P. Chen (eds.) |
| Edizione | [1st ed. 2000.] |
| Pubbl/distr/stampa | Berlin, Germany ; ; New York, New York : , : Springer, , [2000] |
| Descrizione fisica | 1 online resource (475 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Database searching
Database management Data mining |
| ISBN |
1-280-95182-6
9786610951826 3-540-45571-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Keynote Speeches and Invited Talk -- Perspective on Data Mining from Statistical Viewpoints -- Inductive Databases and Knowledge Scouts -- Hyperlink-Aware Mining and Analysis of the Web -- Data Mining Theory -- Polynomial Time Matching Algorithms for Tree-Like Structured Patterns in Knowledge Discovery -- Fast Discovery of Interesting Rules -- Performance Controlled Data Reduction for Knowledge Discovery in Distributed Databases -- Minimum Message Length Criterion for Second-Order Polynomial Model Discovery -- Frequent Itemset Counting Across Multiple Tables -- Frequent Closures as a Concise Representation for Binary Data Mining -- An Optimization Problem in Data Cube System Design -- Exception Rule Mining with a Relative Interestingness Measure -- Feature Selection and Transformation -- Consistency Based Feature Selection -- Feature Selection for Clustering -- A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases -- Missing Value Estimation Based on Dynamic Attribute Selection -- On Association, Similarity and Dependency of Attributes -- Clustering -- Prototype Generation Based on Instance Filtering and Averaging -- A Visual Method of Cluster Validation with Fastmap -- COE: Clustering with Obstacles Entities A Preliminary Study -- Combining Sampling Technique with DBSCAN Algorithm for Clustering Large Spatial Databases -- Predictive Adaptive Resonance Theory and Knowledge Discovery in Databases -- Improving Generalization Ability of Self-Generating Neural Networks Through Ensemble Averaging -- Application of Data Mining -- Attribute Transformations on Numerical Databases -- Efficient Detection of Local Interactions in the Cascade Model -- Extracting Predictors of Corporate Bankruptcy: Empirical Study on Data Mining Methods -- Evaluating Hypothesis-Driven Exception-Rule Discovery with Medical Data Sets -- Discovering Protein Functional Models Using Inductive Logic Programming -- Mining Web Transaction Patterns in an Electronic Commerce Environment -- Association Rules and Related Topics -- Making Use of the Most Expressive Jumping Emerging Patterns for Classification -- Mining Structured Association Patterns from Databases -- Association Rules -- Density-Based Mining of Quantitative Association Rules -- AViz: A Visualization System for Discovering Numeric Association Rules -- Discovering Unordered and Ordered Phrase Association Patterns for Text Mining -- Using Random Walks for Mining Web Document Associations -- Induction -- A Concurrent Approach to the Key-Preserving Attribute-Oriented Induction Method -- Scaling Up a Boosting-Based Learner via Adaptive Sampling -- Adaptive Boosting for Spatial Functions with Unstable Driving Attributes -- Robust Ensemble Learning for Data Mining -- Interactive Visualization in Mining Large Decision Trees -- VQTree: Vector Quantization for Decision Tree Induction -- Making Knowledge Extraction and Reasoning Closer -- Discovery of Relevant Weights by Minimizing Cross-Validation Error -- Efficient and Comprehensible Local Regression -- Information Granules for Spatial Reasoning -- Text, Web, and Graph Mining -- Uncovering the Hierarchical Structure of Text Archives by Using an Unsupervised Neural Network with Adaptive Architecture -- Mining Access Patterns Efficiently from Web Logs -- A Comparative Study of Classification Based Personal E-mail Filtering -- Extension of Graph-Based Induction for General Graph Structured Data -- Text-Source Discovery and GlOSS Update in a Dynamic Web -- Extraction of Fuzzy Clusters from Weighted Graphs -- Text Summarization by Sentence Segment Extraction Using Machine Learning Algorithms. |
| Record Nr. | UNINA-9910144130103321 |
| Berlin, Germany ; ; New York, New York : , : Springer, , [2000] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Knowledge discovery and data mining : current issues and new applications : 4th Pacific-Asia Conference, PAKDD 2000, Kyoto, Japan, April 18-20, 2000 : proceedings / / Takao Terano, Huan Liu, Arbee L.P. Chen (eds.)
| Knowledge discovery and data mining : current issues and new applications : 4th Pacific-Asia Conference, PAKDD 2000, Kyoto, Japan, April 18-20, 2000 : proceedings / / Takao Terano, Huan Liu, Arbee L.P. Chen (eds.) |
| Edizione | [1st ed. 2000.] |
| Pubbl/distr/stampa | Berlin, Germany ; ; New York, New York : , : Springer, , [2000] |
| Descrizione fisica | 1 online resource (475 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Database searching
Database management Data mining |
| ISBN |
1-280-95182-6
9786610951826 3-540-45571-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Keynote Speeches and Invited Talk -- Perspective on Data Mining from Statistical Viewpoints -- Inductive Databases and Knowledge Scouts -- Hyperlink-Aware Mining and Analysis of the Web -- Data Mining Theory -- Polynomial Time Matching Algorithms for Tree-Like Structured Patterns in Knowledge Discovery -- Fast Discovery of Interesting Rules -- Performance Controlled Data Reduction for Knowledge Discovery in Distributed Databases -- Minimum Message Length Criterion for Second-Order Polynomial Model Discovery -- Frequent Itemset Counting Across Multiple Tables -- Frequent Closures as a Concise Representation for Binary Data Mining -- An Optimization Problem in Data Cube System Design -- Exception Rule Mining with a Relative Interestingness Measure -- Feature Selection and Transformation -- Consistency Based Feature Selection -- Feature Selection for Clustering -- A Simple Dimensionality Reduction Technique for Fast Similarity Search in Large Time Series Databases -- Missing Value Estimation Based on Dynamic Attribute Selection -- On Association, Similarity and Dependency of Attributes -- Clustering -- Prototype Generation Based on Instance Filtering and Averaging -- A Visual Method of Cluster Validation with Fastmap -- COE: Clustering with Obstacles Entities A Preliminary Study -- Combining Sampling Technique with DBSCAN Algorithm for Clustering Large Spatial Databases -- Predictive Adaptive Resonance Theory and Knowledge Discovery in Databases -- Improving Generalization Ability of Self-Generating Neural Networks Through Ensemble Averaging -- Application of Data Mining -- Attribute Transformations on Numerical Databases -- Efficient Detection of Local Interactions in the Cascade Model -- Extracting Predictors of Corporate Bankruptcy: Empirical Study on Data Mining Methods -- Evaluating Hypothesis-Driven Exception-Rule Discovery with Medical Data Sets -- Discovering Protein Functional Models Using Inductive Logic Programming -- Mining Web Transaction Patterns in an Electronic Commerce Environment -- Association Rules and Related Topics -- Making Use of the Most Expressive Jumping Emerging Patterns for Classification -- Mining Structured Association Patterns from Databases -- Association Rules -- Density-Based Mining of Quantitative Association Rules -- AViz: A Visualization System for Discovering Numeric Association Rules -- Discovering Unordered and Ordered Phrase Association Patterns for Text Mining -- Using Random Walks for Mining Web Document Associations -- Induction -- A Concurrent Approach to the Key-Preserving Attribute-Oriented Induction Method -- Scaling Up a Boosting-Based Learner via Adaptive Sampling -- Adaptive Boosting for Spatial Functions with Unstable Driving Attributes -- Robust Ensemble Learning for Data Mining -- Interactive Visualization in Mining Large Decision Trees -- VQTree: Vector Quantization for Decision Tree Induction -- Making Knowledge Extraction and Reasoning Closer -- Discovery of Relevant Weights by Minimizing Cross-Validation Error -- Efficient and Comprehensible Local Regression -- Information Granules for Spatial Reasoning -- Text, Web, and Graph Mining -- Uncovering the Hierarchical Structure of Text Archives by Using an Unsupervised Neural Network with Adaptive Architecture -- Mining Access Patterns Efficiently from Web Logs -- A Comparative Study of Classification Based Personal E-mail Filtering -- Extension of Graph-Based Induction for General Graph Structured Data -- Text-Source Discovery and GlOSS Update in a Dynamic Web -- Extraction of Fuzzy Clusters from Weighted Graphs -- Text Summarization by Sentence Segment Extraction Using Machine Learning Algorithms. |
| Record Nr. | UNISA-996465820603316 |
| Berlin, Germany ; ; New York, New York : , : Springer, , [2000] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||