Methodologies for Knowledge Discovery and Data Mining Third Pacific-Asia Conference, PAKDD'99, Beijing, China, April 26-28, 1999, Proceedings /

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Zhong, Ning (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt), Zhou, Lizhu (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1999.
Έκδοση:1st ed. 1999.
Σειρά:Lecture Notes in Artificial Intelligence ; 1574
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Invited Talks
  • KDD as an Enterprise IT Tool: Reality and Agenda
  • Computer Assisted Discovery of First Principle Equations from Numeric Data
  • Emerging KDD Technology
  • Data Mining - a Rough Set Perspective
  • Data Mining Techniques for Associations, Clustering and Classification
  • Data Mining: Granular Computing Approach
  • Rule Extraction from Prediction Models
  • Association Rules
  • Mining Association Rules on Related Numeric Attributes
  • LGen - A Lattice-Based Candidate Set Generation Algorithm for I/O Efficient Association Rule Mining
  • Extending the Applicability of Association Rules
  • An Efficient Approach for Incremental Association Rule Mining
  • Association Rules in Incomplete Databases
  • Parallel SQL Based Association Rule Mining on Large Scale PC Cluster: Performance Comparison with Directly Coded C Implementation
  • H-Rule Mining in Heterogeneous Databases
  • An Improved Definition of Multidimensional Inter-transaction Association Rule
  • Incremental Discovering Association Rules: A Concept Lattice Approach
  • Feature Selection and Generation
  • Induction as Pre-processing
  • Stochastic Attribute Selection Committees with Multiple Boosting: Learning More Accurate and More Stable Classifier Committees
  • On Information-Theoretic Measures of Attribute Importance
  • A Technique of Dynamic Feature Selection Using the Feature Group Mutual Information
  • A Data Pre-processing Method Using Association Rules of Attributes for Improving Decision Tree
  • Mining in Semi, Un-structured Data
  • An Algorithm for Constrained Association Rule Mining in Semi-structured Data
  • Incremental Mining of Schema for Semistructured Data
  • Discovering Structure from Document Databases
  • Combining Forecasts from Multiple Textual Data Sources
  • Domain Knowledge Extracting in a Chinese Natural Language Interface to Databases: NChiql
  • Interestingness, Surprisingness, and Exceptions
  • Evolutionary Hot Spots Data Mining
  • Efficient Search of Reliable Exceptions
  • Heuristics for Ranking the Interestingness of Discovered Knowledge
  • Rough Sets, Fuzzy Logic, and Neural Networks
  • Automated Discovery of Plausible Rules Based on Rough Sets and Rough Inclusion
  • Discernibility System in Rough Sets
  • Automatic Labeling of Self-Organizing Maps: Making a Treasure-Map Reveal Its Secrets
  • Neural Network Based Classifiers for a Vast Amount of Data
  • Accuracy Tuning on Combinatorial Neural Model
  • A Situated Information Articulation Neural Network: VSF Network
  • Neural Method for Detection of Complex Patterns in Databases
  • Preserve Discovered Linguistic Patterns Valid in Volatility Data Environment
  • An Induction Algorithm Based on Fuzzy Logic Programming
  • Rule Discovery in Databases with Missing Values Based on Rough Set Model
  • Sustainability Knowledge Mining from Human Development Database
  • Induction, Classification, and Clustering
  • Characterization of Default Knowledge in Ripple Down Rules Method
  • Improving the Performance of Boosting for Naive Bayesian Classification
  • Convex Hulls in Concept Induction
  • Mining Classification Knowledge Based on Cloud Models
  • Robust Clusterin of Large Geo-referenced Data Sets
  • A Fast Algorithm for Density-Based Clustering in Large Database
  • A Lazy Model-Based Algorithm for On-Line Classification
  • An Efficient Space-Partitioning Based Algorithm for the K-Means Clustering
  • A Fast Clustering Process for Outliers and Remainder Clusters
  • Optimising the Distance Metric in the Nearest Neighbour Algorithm on a Real-World Patient Classification Problem
  • Classifying Unseen Cases with Many Missing Values
  • Study of a Mixed Similarity Measure for Classification and Clustering
  • Visualization
  • Visually Aided Exploration of Interesting Association Rules
  • DVIZ: A System for Visualizing Data Mining
  • Causal Model and Graph-Based Methods
  • A Minimal Causal Model Learner
  • Efficient Graph-Based Algorithm for Discovering and Maintaining Knowledge in Large Databases
  • Basket Analysis for Graph Structured Data
  • The Evolution of Causal Models: A Comparison of Bayesian Metrics and Structure Priors
  • KD-FGS: A Knowledge Discovery System from Graph Data Using Formal Graph System
  • Agent-Based, and Distributed Data Mining
  • Probing Knowledge in Distributed Data Mining
  • Discovery of Equations and the Shared Operational Semantics in Distributed Autonomous Databases
  • The Data-Mining and the Technology of Agents to Fight the Illicit Electronic Messages
  • Knowledge Discovery in SportsFinder: An Agent to Extract Sports Results from the Web
  • Event Mining with Event Processing Networks
  • Advanced Topics and New Methodologies
  • An Analysis of Quantitative Measures Associated with Rules
  • A Strong Relevant Logic Model of Epistemic Processes in Scientific Discovery
  • Discovering Conceptual Differences among Different People via Diverse Structures
  • Ordered Estimation of Missing Values
  • Prediction Rule Discovery Based on Dynamic Bias Selection
  • Discretization of Continuous Attributes for Learning Classification Rules
  • BRRA: A Based Relevant Rectangles Algorithm for Mining Relationships in Databases
  • Mining Functional Dependency Rule of Relational Database
  • Time-Series Prediction with Cloud Models in DMKD.