Methodologies for Knowledge Discovery and Data Mining : Third Pacific-Asia Conference, PAKDD'99, Beijing, China, April 26-28, 1999, Proceedings / edited by Ning Zhong, Lizhu Zhou.

Format:

Book

Contributor:

Zhong, Ning, 1956- editor.

Zhou, Lizhu, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 1574.

Lecture Notes in Artificial Intelligence ; 1574

Language:

English

Subjects (All):

Artificial intelligence.

Database management.

Information storage and retrieval.

Application software.

Information technology.

Business--Data processing.

Business.

Artificial Intelligence.

Database Management.

Information Storage and Retrieval.

Information Systems Applications (incl. Internet).

IT in Business.

Local Subjects:

Artificial Intelligence.

Database Management.

Information Storage and Retrieval.

Information Systems Applications (incl. Internet).

IT in Business.

Physical Description:

1 online resource (XVI, 540 pages).

Edition:

First edition 1999.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1999.

System Details:

text file PDF

Contents:

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.

Other Format:

Printed edition:

ISBN:

978-3-540-48912-2

9783540489122

Access Restriction:

Restricted for use by site license.