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Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001. Proceedings / / edited by David Cheung, Graham J. Williams, Qing Li
| Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001. Proceedings / / edited by David Cheung, Graham J. Williams, Qing Li |
| Edizione | [1st ed. 2001.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 |
| Descrizione fisica | 1 online resource (XVII, 599 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data structures (Computer science)
Artificial intelligence Information storage and retrieval Information technology Business—Data processing Application software Mathematical statistics Data Structures and Information Theory Artificial Intelligence Information Storage and Retrieval IT in Business Information Systems Applications (incl. Internet) Probability and Statistics in Computer Science |
| ISBN | 3-540-45357-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Keynote Presentations -- Incompleteness in Data Mining -- Mining E-Commerce Data: The Good, the Bad, and the Ugly -- Seamless Integration of Data Mining with DBMS and Applications -- Web Mining -- Applying Pattern Mining to Web Information Extraction -- Empirical Study of Recommender Systems Using Linear Classifiers -- iJADE eMiner - A Web-Based Mining Agent Based on Intelligent Java Agent Development Environment (iJADE) on Internet Shopping -- A Characterized Rating Recommend System -- Discovery of Frequent Tree Structured Patterns in Semistructured Web Documents -- Text Mining -- Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification -- Predictive Self-Organizing Networks for Text Categorization -- Meta-learning Models for Automatic Textual Document Categorization -- Efficient Algorithms for Concept Space Construction -- Topic Detection, Tracking, and Trend Analysis Using Self-Organizing Neural Networks -- Automatic Hypertext Construction through a Text Mining Approach by Self-Organizing Maps -- Applications and Tools -- Semantic Expectation-Based Causation Knowledge Extraction: A Study on Hong Kong Stock Movement Analysis -- A Toolbox Approach to Flexible and Efficient Data Mining -- Determining Progression in Glaucoma Using Visual Fields -- Seabreeze Prediction Using Bayesian Networks -- Semi-supervised Learning in Medical Image Database -- On Application of Rough Data Mining Methods to Automatic Construction of Student Models -- Concept Hierarchies -- Concept Approximation in Concept Lattice -- Generating Concept Hierarchies/Networks: Mining Additional Semantics in Relational Data -- Representing Large Concept Hierarchies Using Lattice Data Structure -- Feature Selection -- Feature Selection for Temporal Health Records -- Boosting the Performance of Nearest Neighbour Methods with Feature Selection -- Feature Selection for Meta-learning -- Interestingness -- Efficient Mining of Niches and Set Routines -- Evaluation of Interestingness Measures for Ranking Discovered Knowledge -- Peculiarity Oriented Mining and Its Application for Knowledge Discovery in Amino-Acid Data -- Sequence Mining -- Mining Sequence Patterns from Wind Tunnel Experimental Data for Flight Control -- Scalable Hierarchical Clustering Method for Sequences of Categorical Values -- FFS - An I/O-Efficient Algorithm for Mining Frequent Sequences -- Sequential Index Structure for Content-Based Retrieval -- Spatial and Temporal Mining -- The S 2-Tree: An Index Structure for Subsequence Matching of Spatial Objects -- Temporal Data Mining Using Hidden Markov-Local Polynomial Models -- Patterns Discovery Based on Time-Series Decomposition -- Criteria on Proximity Graphs for Boundary Extraction and Spatial Clustering -- Micro Similarity Queries in Time Series Database -- Association Mining -- Mining Optimal Class Association Rule Set -- Generating Frequent Patterns with the Frequent Pattern List -- User-Defined Association Mining -- Direct and Incremental Computing of Maximal Covering Rules -- Towards Efficient Data Re-mining (DRM) -- Data Allocation Algorithm for Parallel Association Rule Discovery -- Classification and Rule Induction -- Direct Domain Knowledge Inclusion in the PA3 Rule Induction Algorithm -- Hierarchical Classification of Documents with Error Control -- An Efficient Data Compression Approach to the Classification Task -- Combining the Strength of Pattern Frequency and Distance for Classification -- A Scalable Algorithm for Rule Post-pruning of Large Decision Trees -- Optimizing the Induction of Alternating Decision Trees -- Building Behaviour Knowledge Space to Make Classification Decision -- Clustering -- Efficient Hierarchical Clustering Algorithms Using Partially Overlapping Partitions -- A Rough Set-Based Clustering Method with Modification of Equivalence Relations -- Importance of Individual Variables in the k-Means Algorithm -- A Hybrid Approach to Clustering in Very Large Databases -- Advanced Topics and New Methods -- A Similarity Indexing Method for the Data Warehousing - Bit-Wise Indexing Method -- Rule Reduction over Numerical Attributes in Decision Trees Using Multilayer Perceptron -- Knowledge Acquisition from Both Human Expert and Data -- Neighborhood Dependencies for Prediction -- Learning Bayesian Networks with Hidden Variables Using the Combination of EM and Evolutionary Algorithms -- Interactive Construction of Decision Trees -- An Improved Learning Algorithm for Augmented Naive Bayes -- Generalised RBF Networks Trained Using an IBL Algorithm for Mining Symbolic Data. |
| Record Nr. | UNISA-996465775103316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Knowledge Discovery and Data Mining : 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001. Proceedings / / edited by David Cheung, Graham J. Williams, Qing Li
| Advances in Knowledge Discovery and Data Mining : 5th Pacific-Asia Conference, PAKDD 2001 Hong Kong, China, April 16-18, 2001. Proceedings / / edited by David Cheung, Graham J. Williams, Qing Li |
| Edizione | [1st ed. 2001.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 |
| Descrizione fisica | 1 online resource (XVII, 599 p.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data structures (Computer science)
Artificial intelligence Information storage and retrieval Information technology Business—Data processing Application software Mathematical statistics Data Structures and Information Theory Artificial Intelligence Information Storage and Retrieval IT in Business Information Systems Applications (incl. Internet) Probability and Statistics in Computer Science |
| ISBN | 3-540-45357-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Keynote Presentations -- Incompleteness in Data Mining -- Mining E-Commerce Data: The Good, the Bad, and the Ugly -- Seamless Integration of Data Mining with DBMS and Applications -- Web Mining -- Applying Pattern Mining to Web Information Extraction -- Empirical Study of Recommender Systems Using Linear Classifiers -- iJADE eMiner - A Web-Based Mining Agent Based on Intelligent Java Agent Development Environment (iJADE) on Internet Shopping -- A Characterized Rating Recommend System -- Discovery of Frequent Tree Structured Patterns in Semistructured Web Documents -- Text Mining -- Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification -- Predictive Self-Organizing Networks for Text Categorization -- Meta-learning Models for Automatic Textual Document Categorization -- Efficient Algorithms for Concept Space Construction -- Topic Detection, Tracking, and Trend Analysis Using Self-Organizing Neural Networks -- Automatic Hypertext Construction through a Text Mining Approach by Self-Organizing Maps -- Applications and Tools -- Semantic Expectation-Based Causation Knowledge Extraction: A Study on Hong Kong Stock Movement Analysis -- A Toolbox Approach to Flexible and Efficient Data Mining -- Determining Progression in Glaucoma Using Visual Fields -- Seabreeze Prediction Using Bayesian Networks -- Semi-supervised Learning in Medical Image Database -- On Application of Rough Data Mining Methods to Automatic Construction of Student Models -- Concept Hierarchies -- Concept Approximation in Concept Lattice -- Generating Concept Hierarchies/Networks: Mining Additional Semantics in Relational Data -- Representing Large Concept Hierarchies Using Lattice Data Structure -- Feature Selection -- Feature Selection for Temporal Health Records -- Boosting the Performance of Nearest Neighbour Methods with Feature Selection -- Feature Selection for Meta-learning -- Interestingness -- Efficient Mining of Niches and Set Routines -- Evaluation of Interestingness Measures for Ranking Discovered Knowledge -- Peculiarity Oriented Mining and Its Application for Knowledge Discovery in Amino-Acid Data -- Sequence Mining -- Mining Sequence Patterns from Wind Tunnel Experimental Data for Flight Control -- Scalable Hierarchical Clustering Method for Sequences of Categorical Values -- FFS - An I/O-Efficient Algorithm for Mining Frequent Sequences -- Sequential Index Structure for Content-Based Retrieval -- Spatial and Temporal Mining -- The S 2-Tree: An Index Structure for Subsequence Matching of Spatial Objects -- Temporal Data Mining Using Hidden Markov-Local Polynomial Models -- Patterns Discovery Based on Time-Series Decomposition -- Criteria on Proximity Graphs for Boundary Extraction and Spatial Clustering -- Micro Similarity Queries in Time Series Database -- Association Mining -- Mining Optimal Class Association Rule Set -- Generating Frequent Patterns with the Frequent Pattern List -- User-Defined Association Mining -- Direct and Incremental Computing of Maximal Covering Rules -- Towards Efficient Data Re-mining (DRM) -- Data Allocation Algorithm for Parallel Association Rule Discovery -- Classification and Rule Induction -- Direct Domain Knowledge Inclusion in the PA3 Rule Induction Algorithm -- Hierarchical Classification of Documents with Error Control -- An Efficient Data Compression Approach to the Classification Task -- Combining the Strength of Pattern Frequency and Distance for Classification -- A Scalable Algorithm for Rule Post-pruning of Large Decision Trees -- Optimizing the Induction of Alternating Decision Trees -- Building Behaviour Knowledge Space to Make Classification Decision -- Clustering -- Efficient Hierarchical Clustering Algorithms Using Partially Overlapping Partitions -- A Rough Set-Based Clustering Method with Modification of Equivalence Relations -- Importance of Individual Variables in the k-Means Algorithm -- A Hybrid Approach to Clustering in Very Large Databases -- Advanced Topics and New Methods -- A Similarity Indexing Method for the Data Warehousing - Bit-Wise Indexing Method -- Rule Reduction over Numerical Attributes in Decision Trees Using Multilayer Perceptron -- Knowledge Acquisition from Both Human Expert and Data -- Neighborhood Dependencies for Prediction -- Learning Bayesian Networks with Hidden Variables Using the Combination of EM and Evolutionary Algorithms -- Interactive Construction of Decision Trees -- An Improved Learning Algorithm for Augmented Naive Bayes -- Generalised RBF Networks Trained Using an IBL Algorithm for Mining Symbolic Data. |
| Record Nr. | UNINA-9910143597403321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2001 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data Mining [[electronic resource] ] : Theory, Methodology, Techniques, and Applications / / edited by Graham J. Williams, Simeon J. Simoff
| Data Mining [[electronic resource] ] : Theory, Methodology, Techniques, and Applications / / edited by Graham J. Williams, Simeon J. Simoff |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 |
| Descrizione fisica | 1 online resource (XI, 331 p.) |
| Disciplina | 005.74 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Database management
Artificial intelligence Computers Information storage and retrieval Pattern recognition Database Management Artificial Intelligence Computation by Abstract Devices Information Storage and Retrieval Pattern Recognition |
| ISBN | 3-540-32548-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1: State-of-the-Art in Research -- Generality Is Predictive of Prediction Accuracy -- Visualisation and Exploration of Scientific Data Using Graphs -- A Case-Based Data Mining Platform -- Consolidated Trees: An Analysis of Structural Convergence -- K Nearest Neighbor Edition to Guide Classification Tree Learning: Motivation and Experimental Results -- Efficiently Identifying Exploratory Rules’ Significance -- Mining Value-Based Item Packages – An Integer Programming Approach -- Decision Theoretic Fusion Framework for Actionability Using Data Mining on an Embedded System -- Use of Data Mining in System Development Life Cycle -- Mining MOUCLAS Patterns and Jumping MOUCLAS Patterns to Construct Classifiers -- A Probabilistic Geocoding System Utilising a Parcel Based Address File -- Decision Models for Record Linkage -- Intelligent Document Filter for the Internet -- Informing the Curious Negotiator: Automatic News Extraction from the Internet -- Text Mining for Insurance Claim Cost Prediction -- An Application of Time-Changing Feature Selection -- A Data Mining Approach to Analyze the Effect of Cognitive Style and Subjective Emotion on the Accuracy of Time-Series Forecasting -- A Multi-level Framework for the Analysis of Sequential Data -- 2: State-of-the-Art in Applications -- Hierarchical Hidden Markov Models: An Application to Health Insurance Data -- Identifying Risk Groups Associated with Colorectal Cancer -- Mining Quantitative Association Rules in Protein Sequences -- Mining X-Ray Images of SARS Patients -- The Scamseek Project – Text Mining for Financial Scams on the Internet -- A Data Mining Approach for Branch and ATM Site Evaluation -- The Effectiveness of Positive Data Sharing in Controlling the Growth of Indebtedness in Hong Kong Credit Card Industry. |
| Record Nr. | UNISA-996466164103316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Data mining : theory, methodology, techniques, and applications / / Graham J. Williams, Simeon J. Simoff (eds.)
| Data mining : theory, methodology, techniques, and applications / / Graham J. Williams, Simeon J. Simoff (eds.) |
| Edizione | [1st ed. 2006.] |
| Pubbl/distr/stampa | Berlin ; ; New York, : Springer, c2006 |
| Descrizione fisica | 1 online resource (XI, 331 p.) |
| Disciplina | 005.74 |
| Altri autori (Persone) |
WilliamsGraham J
SimoffSimeon J. <1962-> |
| Collana |
LNCS sublibrary. SL 7, Artificial intelligence
State-of-the-art survey Lecture notes in computer science,Lecture notes in artificial intelligence |
| Soggetto topico | Data mining |
| ISBN | 3-540-32548-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | pt. 1. State-of-the-art in research -- pt. 2. State-of-the-art in applications. |
| Record Nr. | UNINA-9910483435503321 |
| Berlin ; ; New York, : Springer, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||