E-raamat: Principles of Data Mining and Knowledge Discovery: Third European Conference, PKDD'99 Prague, Czech Republic, September 15-18, 1999 Proceedings

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.