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Zighed, D.A., Université Lyon 2, Bron, France
Komorowski, J., Norwegian University of Science and Technology, Trondheim, Norway Zytkow, J., University of North Carolina, Charlotte, NC, USA (Eds.) Principles of Data Mining and Knowledge Discovery 4th European Conference, PKDD, 2000, Lyon, France, September 13-16, 2000 Proceedings 2000. XV, 701 pp.
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S1A: Towards broader foundations
Arno J. KNOBBE, Arno SIEBES, Hendrik BLOCKEEL, and Daniël van der WALLEN
Multi-Relational Data Mining, Using UML for ILP
Akihiro INOKUCHI, Takashi WASHIO, and Hiroshi MOTODA
An Apriori-based Algorithm for Mining Frequent Substructures from Graph Data
Maurice BERNADET
Basis of a Fuzzy Knowledge Discovery System
S1B: Rules and trees
Dragan GAMBERGER, and Nada LAVRAC
Confirmation rule sets
Marc SEBBAN, and Richard NOCK
Contribution of Dataset Reduction Techniques to Tree-Simplification and Knowledge Discovery
Ljupco TODOROVSKI, and Saso DZEROSKI
Combining Multiple Models with Meta Decision Trees
S2A: Databases and reward-based learning
Tadeusz MORZY, Marek WOJCIECHOWSKI, and Maciej ZAKRZEWICZ
Materialized Data Mining Views
Jean-François BOULICAUT, Arthur BYKOWSKI, and Christophe RIGOTTI
Approximation of frequency queries by means of free-sets
Paul MUNTEANU, and Denis CAU
Efficient Score-based Learning of Equivalence Classes of Bayesian Networks
Christophe DRUET, Damien ERNST, and Louis WEHENKEL
Application of Reinforcement Learning to Electrical Power System Closed-Loop Emergency Control
S2B: Classification
Melanie HILARIO, and Alexandros KALOUSIS
Quantifying the Resilience of Inductive Classification Algorithms
Alexey TSYMBAL, and Seppo PUURONEN
Bagging and Boosting with Dynamic Integration of Classifiers
Carlos SOARES, and Pavel B. BRAZDIL
Zoomed Ranking: Selection of Classification Algorithms Based on Relevant Performance Information
Pierre GEURTS
Some enhancements of decision tree bagging
S3A: Association rules and exceptions
Marcus-Christopher LUDL, and Gerhard WIDMER
Relative Unsupervised Discretization for Association Rule Mining
Jochen HIPP, Ulrich GÜNTZER, and Gholamreza NAKHAEIZADEH
Mining Association Rules: Deriving a Superior Algorithm by Analysing Today's Approaches
Einoshin SUZUKI, and Jan ZYTKOW
Unified Algorithm for Undirected Discovery of Exception Rules
Jean-Hugues CHAUCHAT, Ricco RAKOTOMALALA, and Didier ROBERT
Sampling Strategies for targeting rare groups from a bank customer database
S3B: Instance-based discovery
Jinyan LI, Guozhu DONG, and Kotagiri RAMAMOHANARAO
Instance-Based Classification by Emerging Patterns
Gautam DAS, and Heikki MANNILA
Context-Based Similarity Measures for Categorical Databases
Ngoc Binh NGUYEN, and Tu Bao HO
A Mixed Similarity Measure in Near-Linear Computational Complexity for Distance-based Methods
Stéphane LALLICH, and Ricco RAKOTOMALALA
Fast feature selection using partial correlation for multi-valued attributes
S4A: Clustering and classification
Markus M. BREUNIG, Hans-Peter KRIEGEL, and Jörg SANDER
Fast Hierarchical Clustering Based on Compressed Data and OPTICS
Ljupco TODOROVSKI, Peter FLACH, and Nada LAVRAC
Predictive Performance of Weighted Relative Accuracy
Bin ZHANG, Meichun HSU, and George FORMAN
Accurate Recasting of Parameter Estimation Algorithms using Sufficient Statistics for Efficient Parallel Speed-up Demonstrated for Center-Based Data Clustering Algorithms
Maria HALKIDI, M. VAZIRGIANNIS, and Y. BATISTAKIS
Quality scheme assessment in the clustering process
S5A: Time Series
Iztok SAVNIK, Georg LAUSEN, Hans-Peter KAHLE, Heinrich SPIECKER, and Sebastian HEIN
Algorithm for Matching Sets of Time Series
Georg LAUSEN, Iztok SAVNIK, and Aldar DOUGARJAPOV
MSTS: A System for Mining Sets of Time Series
Juan J. RODRIGUEZ, Carlos J. ALONSO, and Henrik BOSTRÖM
Learning First Order Logic Time Series Classifiers : Rules and Boosting
Short Papers / Posters
Zighed, D.A., Université Lyon 2, Bron, France
Komorowski, J., Norwegian University of Science and Technology, Trondheim, Norway
Zytkow, J., University of North Carolina, Charlotte, NC, USA
(Eds.)
Principles of Data Mining and Knowledge Discovery
4th European Conference, PKDD, 2000, Lyon, France, September 13-16, 2000 Proceedings
2000. XV, 701 pp.
3-540-41066-X
Recommanded price: 146 DM - FF 550 - £ 50,50
Springer-Verlag Publisher
Sylvia ACID, and Luis M. DE CAMPOS
Learning Right Sized Belief Networks by Means of a Hybrid Methodology
Brock BARBER, and Howard J. HAMILTON
Algorithms for Mining Share Frequent Itemsets Containing Infrequent Subsets
Hilan BENSUSAN, and Christophe GIRAUD-CARRIER
Discovering task neighbourhoods through landmark learning performances
Leon BOBROWSKI, and Marek KRETOWSKI
Induction of Multivariate Decision Trees by using Dipolar Criteria
Sam BREWER, and Tom KHABAZA
Inductive Logic Programming in Clementine
Deborah R. CARVALHO, and Alex A. FREITAS
A genetic algorithm-based solution for the problem of small disjuncts
Antonio CIAMPI, and Yves LECHEVALLIER
Clustering Large, Multi-Level Data Sets: An Approach Based On Kohonen Self Organizing Maps
Antonio CIAMPI, Djamel A. ZIGHED, and Jérémy CLECH
Trees and induction graphs for multivariate response
Richard COLE, Peter EKLUND, and Gerd STUMME
CEM - Visualisation and Discovery in Email
Chabane DJERABA
Image access and data mining: an approach
Nikos DROSSOS, Athanasios PAPAGELIS, and Dimitris KALLES
Decision Tree Toolkit: A Component-based Library of Decision Tree Algorithms
Laurent DURY, Laurence LEHERTE, and Daniel P. VERCAUTEREN
Determination of Screening Descriptors for Chemical Reaction Databases
A. J. FEELDERS
Prior knowledge in economic applications of data mining
Pierre GEURTS, and Louis WEHENKEL
Temporal machine learning for switching control
David GROSSER, Jean DIATTA, and Noël CONRUYT
Improving Dissimilarity Functions with Domain Knowledge, applications with IKBS system
Attila GYENESEI
Mining Weighted Association Rules for Fuzzy Quantitative Items
Eui-Hong (Sam) HAN, and George KARYPIS
Centroid-Based Document Classification: Analysis & Experimental Results
Robert J. HILDERMAN, and Howard J. HAMILTON
Applying Objective Interestingness Measures in Data Mining Systems
Martin HOLENA
Observational Logic Integrates Data Mining Based on Statistics and Neural Networks
Dimitar HRISTOVSKI, Saso DZEROSKI, Borut PETERLIN, and Anamarija ROZIC-HRISTOVSKI
Supporting Discovery in Medicine by Association Rule Mining of Bibliographic Databases
Hillol KARGUPTA, Weiyun HUANG, Krishnamoorthy SIVAKUMAR, Byung-Hoon PARK, and Shuren WANG
Collective Principal Component Analysis from Distributed, Heterogeneous Data
Saori KAWASAKI, Ngoc Binh NGUYEN, and Tu Bao HO
Hierarchical Document Clustering Based on Tolerance Rough Set Model
Jörg KELLER, Valerij BAUER, and Wojciech KWEDLO
Application of Data-Mining and Knowledge Discovery in Automotive Data Engineering
Jan KOMOROWSKI, Torgeir R. HVIDSTEN, Tor-Kristian JENSSEN, Dyre TJELDVOLL, Eivind HOVIG,
Arne K. SANVIK, and Astrid LAEGREID
Towards Knowledge Discovery from cDNA Microarray Gene Expression Data
Marzena KRYSZKIEWICZ
Mining with Cover and Extension Operators
Pascale KUNTZ, Fabrice GUILLET, Rémi LEHN, and Henri BRIAND
A User-Driven Process for Mining Association Rules
Carsten LANQUILLON
Learning from Labeled and Unlabeled Documents: A comparative study on semi-supervised text classification
P.A. LAUR, F. MASSEGLIA, and P. PONCELET
Schema Mining: Finding Structural Regularity among Semistructured Data
Bing LIU, Yiming MA , and Ching Kian WONG
Improving an Association Rule Based Classifier
Chung-Leung LUI, and Fu-Lai CHUNG
Discovery of generalized association rules with multiple minimum supports
Adele MARSHALL, Sally McCLEAN, Mary SHAPCOTT, and Peter MILLARD
Learning Dynamic Bayesian Belief Network using Conditional Phase-Type Distributions
José F. MARTINEZ-TRINIDAD, Miriam VELASCO-SANCHEZ, and Edgar E. CONTRERAS-ARAVELO
Discovering differences in patients with uveitis through typical testors by class
F. MASSEGLIA, P. PONCELET, and M. TEISSEIRE
Web Usage Mining: how to Efficiently manage New transactions and new clients
Frédéric MOAL, Teddy TURMEAUX, and Christel VRAIN
Mining Relational Databases
Maybin K. MUYEBA, and John A. KEANE
Interestingness In Attribute-Oriented Induction (AOI): Multiple-level Rule Generation
Takashi OKADA, and Mayumi OYAMA
Discovery of Characteristic Subgraph Patterns using Relative Indexing and the Cascade Model
Gerhard PAASS, and Jorg KINDERMANN
Transparency and Predictive Power. Explaining Complex Classification Models
Srinivasan PARTHASARATHY, and Mitsunori OGIHARA
Clustering Homogeneous Datasets for Distributed Mining
Petra PERNER, and Chid APTE
Empirical Evaluation of Feature Subset Selection based on a Real-World Data Set
Gerard RAMSTEIN, Pascal BUNELLE, and Yannick JACQUES
Discovery of ambiguous patterns in sequences. Application to bioinformatics
Zbigniew W. RAS, and Alicja WIECZORKOWSKA
Action-Rules : how to increase profit of a company
Gilbert RITSCHARD, and Nicolas NICOLOYANNIS
Aggregation and Association in Cross Tables
Céline ROBARDET, Fabien FESCHET, and Nicolas NICOLOYANNIS
An experimental study of partition quality indices in clustering
Fabrice ROSSI, and Frédérick VAUTRAIN
Expert Constrained Clustering: a Symbolic Approach
Ansaf SALLEB, and Christel VRAIN
An Application of Association Rules Discovery to Geographic Information Systems
Dan A. SIMOVICI, Dana CRISTOFOR, and Laurentiu CRISTOFOR
Generalized Entropy and Projection Clustering of Categorical Data
Vojtech SVATEK, and Martin KAVALEC
Supporting Case Acquisition and Labelling in the Context of Web Mining
Pang-Ning TAN, Vipin KUMAR, and Jaideep SRIVASTAVA
Indirect Association: Mining Higher Order Dependencies in Data
Tudor TEUSAN, Gilles NACHOUKI, Henri BRIAND and Jacques PHILIPPE
Discovering Association Rules in Large, Dense Databases
Peter TSELIOS, Agapios PLATIS, and George VOUROS
Providing advice to Website Designers towards effective websites re-organization
Shusaku TSUMOTO
Clinical Knowledge Discovery in Hospital Information Systems: Two Case Studies
Stijn VIAENE, B. BAESENS, T. VAN GESTEL, J.A.K. SUYKENS, D. VAN DEN POEL, J. VANTHIENEN,
D. DE MOOR, and G. DEDENE
Knowledge discovery using Least Squares Support Vector Machine Classifiers: a Direct Marketing Case
Sholom M. WEISS, Brian F. WHITE, and Chidanand V. APTE
Lightweight Document Clustering
Hsin-Chang YANG, and Chung-Hong LEE
Automatic Category Structure Generation and Categorization of Chinese Text Documents
Show-Jane YEN
Mining Generalized Multiple-Level Association Rules
Show-Jane YEN, and Chung-Wen CHO
An Efficient Approach to Discovering Sequential Patterns from Large Databases
Ning ZHONG, Juzhen DONG, and Setsuo OHSUGA
Using Background Knowledge as a Bias to Control the Rule Discovery Process
Workshops
Workshop 1
Data Mining, Decision Support, Meta-learning and ILP:
Forum for Practical Problem
Pavel Brazdil and Alipio Jorge (University of Porto, Portugal)
Meta-Learning
Evaluation of Machine-Learning Algorithm Ranking Advisors
Helmut Berrer, Iain Paterson, Jörg Keller
Meta-Analysis: From data Characterisation for Meta-Learning to Meta-Regression
Christian Köpf, Charles Taylor, Jörg Keller
Report on the Experiments with Feature Selection in Meta-Level Learning
Ljupco Todorovski, Pavel Brazdil, Carlos Soares
Inductive Logic Programming (ILP) for KDD
Towards Practical Inductive Logic Programming
Luc de Raedt
A First-order Representation for Knowledge Discovery and Bayesian Classification on Relational Data
Nicolas Lachiche, Peter A. Flach
Cumulativity as Inductive Bias
Hendrik Blockeel, Luc Dehaspe
Using Inductive Logic Programming to Assist in the Retrieval of Relevant Information from an Electronic Library System
William T. H. Loggie
Demo of Data Mining Software
Demo of D-Miner
Dietrich Wettschereck
Pre-Processing for KDD
How to Preprocess Large Databases
Regina Zücker, Jörg-Uwe Kietz
The Principal Component Method as a Preprocesing Stage for Decision Tree Learning
Lubos Popelinsky, Pavel Brazdil
KDD & Data Mining for Decision Support
KDD in Telecommunications
Filip Zelezny, Petr Miksovsky, Olga Stepankova, Jiri Zidek
Enhancing e-Bussiness Through Web Data Mining
Amy Shi, Allen Long, David Newcomb
Advances in Data Mining
A Study on Rule Extraction from Neural Networks Applied to Medical Databases
Guido Bologna
A Data Analysis Approach based on a Neural Networks Data Sets Decomposition and it's Hardware Implementation
Kurosh Madani, Abdennasser Chebira
User-Centric Mining of Association Rules
S K Gupta, Vasudha Bhatnagar, S K Wasan
Workshop 2
Temporal, Spatial and Spatio-Temporal Data Mining (TSDM2000)
John F. Roddick (Flinders U., South Australia)
and Kathleen Hornsby (U. Maine, USA)
Warning: The papers of this workshop are not available on
PKDD2000 website because the TSDM2000 workshop proceeding will be published by
Springer-Verlag.
Discovering Temporal Patterns in Multiple Granularities
Y Li, X.S. Wang, S. Jajodia
Refined Time Stamps for Concept Drift Detection During Mining for Classification Rules
R. Hickey, and M.M. Black
K-Harmonic Means: A Spatial Clustering Algorithm With Boosting
B. Zhang, M. Hsu, and U. Dayal
Identifying Temporal Patterns for Characterization and Prediction of Financial Time Series Events
R. Povinelli
Value Range Queries on Earth Science Data via Histogram Clustering
R. Yang, K.-S. Yang, M. Kafatos, and X.S.Wang
Fast Randomized Algorithms for Robust Estimation of Location
V. Estivill-Castro, and M. Houle
Rough Sets in Spatio-Temporal Data Mining
T. Bittner
Join Indices as a Tool for Spatial Data Mining
K. Zeitouni, L. Yeh, and M-A. Aufaure
Data Mining with Calendar Attributes
H.J. Hamilton, D.J. Randall, and R.J. Hilderman
AUTOCLUST+: Automatic Clustering of Point-Data Sets in the Presence of Obstacles
V. Estivill-Castro and I. Lee
Workshop 3
Knowledge Discovery in Biology
Jan Komorowski (Norwegian University of Science and Technology, Trondheim, Norway)
Opportunities for Data Mining and Knowledge Discovery in Genomic Data
Steffen Schulze-Kremer
Data Mining and Knowledge Discovery in the Pharmaceutical Industry: A grand challenge
Magnus L. Andersson
Data Mining in Gene Expression Data Sets
Yudong He
A Methodology for Knowledge Discovery from Gene Expressions
Torgeir Hvidsten
Protein-Protein InteractionPrediction for C. elegans
Nicolas Thierry-Mieg
Knowledge Discovery from a literature network of human genes for gene-expression analysis
Lisa Öberg
Data Enrichment opf Molecular Structure: Data Mining within Conformational Analysis
Tobias Galliat
(Download1, download2)
Workshop 4
Machine Learning and Textual Information Access
Hugo Zaragoza (LIP6, University Paris 6, France),
Patrick Gallinari (LIP6, University Paris 6, France) and
Martin Rajman (EPFL, Switzerland)
Learning to Filter Spam E-Mail:
A Comparison of a Naive Bayesian and a Memory-Based Approach
I. Androutsopoulos, G. Paliouras, V. Karkaletsis, G. Sakkis, C. D. Syropoulos and P. Stanatopoulos
Short Document Categorization- Itemsets Method
J. Hynek, K.. Jezek and O. J Rohlik
A bootstrapping approach for thematic analysis
O. Ferret and B. Grau
A trainable algorithm for summarizing news stories
J. L. Neto, A. D. Santos, C. A. A. Kaestner, A. A. Freitas, J. C. Nievola
Interactive Learning for Text Summarization
M. R. Amini
Relations between Terms Discovered by Association Rules
M. H. Haddad, J. P. Chevallet, M. F. Bruandet
Multi-class Text Categorization with Error Correcting Codes
J. Kindermann, E. Leopold and G. Paass
Text Classification using String Kernels
H. Lodhi, J. Shawe-Taylor, N. Cristianini, C. Watkins
Information Visualization and Analysis for Knowledge Discovery:
Using a Multi Self-Organizing Mapping
C. François, X. Polanco, J.C. Lamirel
Document Classification and Visualization to Support the Investigation of Suspected Fraud
J. Hangman, D. Perrotta, R. Steinberger and A. Varfis
Workshop 5
Knowledge Management: Theory and Applications
Jean-Louis Ermine (CEA Paris, France)
Introduction
Contents
Challenges and Approaches for Knowledge Management in Companies
Jean-Louis Ermine
Knowledge Management in PSA Peugeot Citroen for Designing Complex products
Patrick Coustillière
A Knowledge Maturity model : a First Approach to Knowledge Management
Cécile Decamps, and Jean-Luc Plet
Samanta : A Knowledge Server
Pascal Vandekerckhove, and Fabrice Guillet
Designing knowledge spaces that work for work - the relationship between physical,
virtual and psychological spaces for knowledge management
Victoria Ward, and Clive Holtham
Interenterprise cooperative information systems for knowledge management
Imed Boughzala, Manuel Zacklad, and Nada Matta
A multi-agent system using semantic metadata for the cooperation
among multiple information sources
Gilles Dubois, and Danielle Boulanger
Scattered Naive Theories: Why the human mind is isomorphic to the internet web
David Leiser
Knowledge Management and Scientific Observation
Thierno Tounkara, and Philippe Benhamou
Relative Measure for Mining Interesting Rules
Farhad Hussain, Huan Liu, and Hongjun Lu
Process Knowledge Management for Activity Support
Pierre Maret
An XML Framework proposal for knowledge discovery in databases
Petr Kotasek, and Jaroslav Zendulka
University knowledge management - issues and prospects
Jaroslava Mikulecká, and Peter Mikulecký
An Appoach to Text Mining using Information extraction
H. Karanikas, C. Tjortjis, and B. Theodoulidis.
Workshop 6
Symbolic Data Analysis:
Theory, Software and Applications for Knowledge Mining
Edwin Diday (University of Paris Dauphine, France)
Preface of PKDD'2000 Workshop on Symbolic Data Analysis
E. Diday and O. Rodriguez
Knowledge discovery from symbolic data and the SODAS software
E. Diday
Symbolic Analysis of Financial Data
F. Goupil, M. Touati, E. Diday and H. Van Der Veen
Generalization of the Principal Components Analysis to Histogram Data
O. Rodriguez, E. Diday and S. Winsberg
Symbolic Representation of Long Time-Series
G. Hebrail and B. Hugueney
Pyramidal Clustering Algorithms in ISO-3D Project
O. Rodriguez and E. Diday
Clustering Large Datasets and Visualizations of Large Hierarchies and Pyramids: Symbolic Data Analysis Approach
V. Batagelj, E. Pavletic, M. Zavernik and S. Korenjak-Cerne
Temporal Symbolic Descriptions Graphics in ISO-3D
M. Noirhomme, A. Nahimana and C. Mazel
Marking and Generalization by Symbolic Descriptions in the Symbolic Official Data Analysis Software
M. Gettler-Summa
Tutorials
Tutorial 1
An Introduction to Distributed Data Mining
H. Kargupta (Washington State University, USA)
Tutorial 2
Clustering Techniques for large Data Sets:
from the past to the future
A. Hinneburg and D. A. Keim (University of Halle, Germany)
Tutorial 3
Data Analysis for Web Marketing
and Merchandizing Applications
Myra Spiliopoulou (Humboldt Universitat zu Berlin, Germany)
Komorowski, J., Norwegian University of Science and Technology, Trondheim, Norway
Zytkow, J., University of North Carolina, Charlotte, NC, USA
(Eds.)
Principles of Data Mining and Knowledge Discovery
4th European Conference, PKDD, 2000, Lyon, France, September 13-16, 2000 Proceedings
2000. XV, 701 pp.
3-540-41066-X
Recommanded price: 146 DM - FF 550 - £ 50,50
Springer-Verlag Publisher
Learning Right Sized Belief Networks by Means of a Hybrid Methodology
Algorithms for Mining Share Frequent Itemsets Containing Infrequent Subsets
Discovering task neighbourhoods through landmark learning performances
Induction of Multivariate Decision Trees by using Dipolar Criteria
Inductive Logic Programming in Clementine
A genetic algorithm-based solution for the problem of small disjuncts
Clustering Large, Multi-Level Data Sets: An Approach Based On Kohonen Self Organizing Maps
Trees and induction graphs for multivariate response
CEM - Visualisation and Discovery in Email
Image access and data mining: an approach
Decision Tree Toolkit: A Component-based Library of Decision Tree Algorithms
Determination of Screening Descriptors for Chemical Reaction Databases
Prior knowledge in economic applications of data mining
Temporal machine learning for switching control
Improving Dissimilarity Functions with Domain Knowledge, applications with IKBS system
Mining Weighted Association Rules for Fuzzy Quantitative Items
Centroid-Based Document Classification: Analysis & Experimental Results
Applying Objective Interestingness Measures in Data Mining Systems
Observational Logic Integrates Data Mining Based on Statistics and Neural Networks
Supporting Discovery in Medicine by Association Rule Mining of Bibliographic Databases
Collective Principal Component Analysis from Distributed, Heterogeneous Data
Hierarchical Document Clustering Based on Tolerance Rough Set Model
Application of Data-Mining and Knowledge Discovery in Automotive Data Engineering
Mining with Cover and Extension Operators
A User-Driven Process for Mining Association Rules
Learning from Labeled and Unlabeled Documents: A comparative study on semi-supervised text classification
Schema Mining: Finding Structural Regularity among Semistructured Data
Improving an Association Rule Based Classifier
Discovery of generalized association rules with multiple minimum supports
Learning Dynamic Bayesian Belief Network using Conditional Phase-Type Distributions
Discovering differences in patients with uveitis through typical testors by class
Web Usage Mining: how to Efficiently manage New transactions and new clients
Mining Relational Databases
Interestingness In Attribute-Oriented Induction (AOI): Multiple-level Rule Generation
Discovery of Characteristic Subgraph Patterns using Relative Indexing and the Cascade Model
Transparency and Predictive Power. Explaining Complex Classification Models
Clustering Homogeneous Datasets for Distributed Mining
Empirical Evaluation of Feature Subset Selection based on a Real-World Data Set
Discovery of ambiguous patterns in sequences. Application to bioinformatics
Action-Rules : how to increase profit of a company
Aggregation and Association in Cross Tables
An experimental study of partition quality indices in clustering
Expert Constrained Clustering: a Symbolic Approach
An Application of Association Rules Discovery to Geographic Information Systems
Generalized Entropy and Projection Clustering of Categorical Data
Supporting Case Acquisition and Labelling in the Context of Web Mining
Indirect Association: Mining Higher Order Dependencies in Data
Discovering Association Rules in Large, Dense Databases
Providing advice to Website Designers towards effective websites re-organization
Clinical Knowledge Discovery in Hospital Information Systems: Two Case Studies
Knowledge discovery using Least Squares Support Vector Machine Classifiers: a Direct Marketing Case
Lightweight Document Clustering
Automatic Category Structure Generation and Categorization of Chinese Text Documents
Mining Generalized Multiple-Level Association Rules
An Efficient Approach to Discovering Sequential Patterns from Large Databases
Using Background Knowledge as a Bias to Control the Rule Discovery Process
Workshop 1
Data Mining, Decision Support, Meta-learning and ILP:
Forum for Practical Problem
Pavel Brazdil and Alipio Jorge (University of Porto, Portugal)
Meta-Learning
Evaluation of Machine-Learning Algorithm Ranking Advisors
Helmut Berrer, Iain Paterson, Jörg Keller
Meta-Analysis: From data Characterisation for Meta-Learning to Meta-Regression
Christian Köpf, Charles Taylor, Jörg Keller
Report on the Experiments with Feature Selection in Meta-Level Learning
Ljupco Todorovski, Pavel Brazdil, Carlos Soares
Inductive Logic Programming (ILP) for KDD
Towards Practical Inductive Logic Programming
Luc de Raedt
A First-order Representation for Knowledge Discovery and Bayesian Classification on Relational Data
Nicolas Lachiche, Peter A. Flach
Cumulativity as Inductive Bias
Hendrik Blockeel, Luc Dehaspe
Using Inductive Logic Programming to Assist in the Retrieval of Relevant Information from an Electronic Library System
William T. H. Loggie
Demo of Data Mining Software
Demo of D-Miner
Dietrich Wettschereck
Pre-Processing for KDD
How to Preprocess Large Databases
Regina Zücker, Jörg-Uwe Kietz
The Principal Component Method as a Preprocesing Stage for Decision Tree Learning
Lubos Popelinsky, Pavel Brazdil
KDD & Data Mining for Decision Support
KDD in Telecommunications
Filip Zelezny, Petr Miksovsky, Olga Stepankova, Jiri Zidek
Enhancing e-Bussiness Through Web Data Mining
Amy Shi, Allen Long, David Newcomb
Advances in Data Mining
A Study on Rule Extraction from Neural Networks Applied to Medical Databases
Guido Bologna
A Data Analysis Approach based on a Neural Networks Data Sets Decomposition and it's Hardware Implementation
Kurosh Madani, Abdennasser Chebira
User-Centric Mining of Association Rules
S K Gupta, Vasudha Bhatnagar, S K Wasan
Workshop 2
Temporal, Spatial and Spatio-Temporal Data Mining (TSDM2000)
John F. Roddick (Flinders U., South Australia)
and Kathleen Hornsby (U. Maine, USA)
Warning: The papers of this workshop are not available on PKDD2000 website because the TSDM2000 workshop proceeding will be published by Springer-Verlag.
Discovering Temporal Patterns in Multiple Granularities
Y Li, X.S. Wang, S. Jajodia
Refined Time Stamps for Concept Drift Detection During Mining for Classification Rules
R. Hickey, and M.M. Black
K-Harmonic Means: A Spatial Clustering Algorithm With Boosting
B. Zhang, M. Hsu, and U. Dayal
Identifying Temporal Patterns for Characterization and Prediction of Financial Time Series Events
R. Povinelli
Value Range Queries on Earth Science Data via Histogram Clustering
R. Yang, K.-S. Yang, M. Kafatos, and X.S.Wang
Fast Randomized Algorithms for Robust Estimation of Location
V. Estivill-Castro, and M. Houle
Rough Sets in Spatio-Temporal Data Mining
T. Bittner
Join Indices as a Tool for Spatial Data Mining
K. Zeitouni, L. Yeh, and M-A. Aufaure
Data Mining with Calendar Attributes
H.J. Hamilton, D.J. Randall, and R.J. Hilderman
AUTOCLUST+: Automatic Clustering of Point-Data Sets in the Presence of Obstacles
V. Estivill-Castro and I. Lee
Workshop 3
Knowledge Discovery in Biology
Jan Komorowski (Norwegian University of Science and Technology, Trondheim, Norway)
Opportunities for Data Mining and Knowledge Discovery in Genomic Data
Steffen Schulze-Kremer
Data Mining and Knowledge Discovery in the Pharmaceutical Industry: A grand challenge
Magnus L. Andersson
Data Mining in Gene Expression Data Sets
Yudong He
A Methodology for Knowledge Discovery from Gene Expressions
Torgeir Hvidsten
Protein-Protein InteractionPrediction for C. elegans
Nicolas Thierry-Mieg
Knowledge Discovery from a literature network of human genes for gene-expression analysis
Lisa Öberg
Data Enrichment opf Molecular Structure: Data Mining within Conformational Analysis
Tobias Galliat (Download1, download2)
Workshop 4
Machine Learning and Textual Information Access
Hugo Zaragoza (LIP6, University Paris 6, France),
Patrick Gallinari (LIP6, University Paris 6, France) and
Martin Rajman (EPFL, Switzerland)
Learning to Filter Spam E-Mail:
A Comparison of a Naive Bayesian and a Memory-Based Approach
I. Androutsopoulos, G. Paliouras, V. Karkaletsis, G. Sakkis, C. D. Syropoulos and P. Stanatopoulos
Short Document Categorization- Itemsets Method
J. Hynek, K.. Jezek and O. J Rohlik
A bootstrapping approach for thematic analysis
O. Ferret and B. Grau
A trainable algorithm for summarizing news stories
J. L. Neto, A. D. Santos, C. A. A. Kaestner, A. A. Freitas, J. C. Nievola
Interactive Learning for Text Summarization
M. R. Amini
Relations between Terms Discovered by Association Rules
M. H. Haddad, J. P. Chevallet, M. F. Bruandet
Multi-class Text Categorization with Error Correcting Codes
J. Kindermann, E. Leopold and G. Paass
Text Classification using String Kernels
H. Lodhi, J. Shawe-Taylor, N. Cristianini, C. Watkins
Information Visualization and Analysis for Knowledge Discovery:
Using a Multi Self-Organizing Mapping
C. François, X. Polanco, J.C. Lamirel
Document Classification and Visualization to Support the Investigation of Suspected Fraud
J. Hangman, D. Perrotta, R. Steinberger and A. Varfis
Workshop 5
Knowledge Management: Theory and Applications
Jean-Louis Ermine (CEA Paris, France)
Introduction
Contents
Challenges and Approaches for Knowledge Management in Companies Jean-Louis Ermine
Knowledge Management in PSA Peugeot Citroen for Designing Complex products
Patrick Coustillière
A Knowledge Maturity model : a First Approach to Knowledge Management
Cécile Decamps, and Jean-Luc Plet
Samanta : A Knowledge Server
Pascal Vandekerckhove, and Fabrice Guillet
Designing knowledge spaces that work for work - the relationship between physical,
virtual and psychological spaces for knowledge management
Victoria Ward, and Clive Holtham
Interenterprise cooperative information systems for knowledge management
Imed Boughzala, Manuel Zacklad, and Nada Matta
A multi-agent system using semantic metadata for the cooperation
among multiple information sources
Gilles Dubois, and Danielle Boulanger
Scattered Naive Theories: Why the human mind is isomorphic to the internet web
David Leiser
Knowledge Management and Scientific Observation
Thierno Tounkara, and Philippe Benhamou
Relative Measure for Mining Interesting Rules
Farhad Hussain, Huan Liu, and Hongjun Lu
Process Knowledge Management for Activity Support
Pierre Maret
An XML Framework proposal for knowledge discovery in databases
Petr Kotasek, and Jaroslav Zendulka
University knowledge management - issues and prospects
Jaroslava Mikulecká, and Peter Mikulecký
An Appoach to Text Mining using Information extraction
H. Karanikas, C. Tjortjis, and B. Theodoulidis.
Workshop 6
Symbolic Data Analysis:
Theory, Software and Applications for Knowledge Mining
Edwin Diday (University of Paris Dauphine, France)
Preface of PKDD'2000 Workshop on Symbolic Data Analysis
E. Diday and O. Rodriguez
Knowledge discovery from symbolic data and the SODAS software
E. Diday
Symbolic Analysis of Financial Data
F. Goupil, M. Touati, E. Diday and H. Van Der Veen
Generalization of the Principal Components Analysis to Histogram Data
O. Rodriguez, E. Diday and S. Winsberg
Symbolic Representation of Long Time-Series
G. Hebrail and B. Hugueney
Pyramidal Clustering Algorithms in ISO-3D Project
O. Rodriguez and E. Diday
Clustering Large Datasets and Visualizations of Large Hierarchies and Pyramids: Symbolic Data Analysis Approach
V. Batagelj, E. Pavletic, M. Zavernik and S. Korenjak-Cerne
Temporal Symbolic Descriptions Graphics in ISO-3D
M. Noirhomme, A. Nahimana and C. Mazel
Marking and Generalization by Symbolic Descriptions in the Symbolic Official Data Analysis Software
M. Gettler-Summa
Tutorials
Tutorial 1
An Introduction to Distributed Data Mining
H. Kargupta (Washington State University, USA)
An Introduction to Distributed Data Mining
H. Kargupta (Washington State University, USA)
Tutorial 2
Clustering Techniques for large Data Sets:
from the past to the future
A. Hinneburg and D. A. Keim (University of Halle, Germany)
Data Analysis for Web Marketing and Merchandizing Applications
Myra Spiliopoulou (Humboldt Universitat zu Berlin, Germany)
