4. PKDD 2000: Lyon, France

Session 1A - Towards Broader Foundations

• Arno J. Knobbe, Arno Siebes, Hendrik Blockeel, Danïel van der Wallen:
  Multi-Relational Data Mining, Using UML for ILP. 1-12
  
• Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda:
  An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data. 13-23
  
• Maurice Bernadet:
  Basis of Fuzzy Knowledge Discovery System. 24-33
  

Session 1B - Rules and Trees

• Dragan Gamberger, Nada Lavrac:
  Confirmation Rule Sets. 34-43
  
• Marc Sebban, Richard Nock:
  Contribution of Dataset Reduction Techniques to Tree-Simplification and Knowledge Discovery. 44-53
  
• Ljupco Todorovski, Saso Dzeroski:
  Combining Multiple Models with Meta Decision Trees. 54-64
  

Session 2A - Databases and Reward-Based Learning

• Tadeusz Morzy, Marek Wojciechowski, Maciej Zakrzewicz:
  Materialized Data Mining Views. 65-74
  
• Jean-François Boulicaut, Artur Bykowski, Christophe Rigotti:
  Approximation of Frequency Queris by Means of Free-Sets. 75-85
  
• Christophe Druet, Damien Ernst, Louis Wehenkel:
  Application of Reinforcement Learning to Electrical Power System Closed-Loop Emergency Control. 86-95
  
• Paul Munteanu, Denis Cau:
  Efficient Score-Based Learning of Equivalence Classes of Bayesian Networks. 96-105
  

Session 2B - Classification

• Melanie Hilario, Alexandros Kalousis:
  Quantifying the Resilience of Inductive Classification Algorithms. 106-115
  
• Alexey Tsymbal, Seppo Puuronen:
  Bagging and Boosting with Dynamic Integration of Classifiers. 116-125
  
• Carlos Soares, Pavel Brazdil:
  Zoomed Ranking: Selection of Classification Algorithms Based on Relevant Performance Information. 126-135
  
• Pierre Geurts:
  Some Enhencements of Decision Tree Bagging. 136-147
  

Session 3A - Association Rules and Exeptions

• Marcus-Christopher Ludl, Gerhard Widmer:
  Relative Unsupervised Discretization for Association Rule Mining. 148-158
  
• Jochen Hipp, Ulrich Güntzer, Gholamreza Nakhaeizadeh:
  Mining Association Rules: Deriving a Superior Algorithm by Analyzing Today's Approaches. 159-168
  
• Einoshin Suzuki, Jan M. Zytkow:
  Unified Algorithm for Undirected Discovery of Execption Rules. 169-180
  
• Jean-Hugues Chauchat, Ricco Rakotomalala, Didier Robert:
  Sampling Strategies for Targeting Rare Groups from a Bank Customer Database. 181-190
  

Session 3B - Instance-Based Discovery

• Jinyan Li, Guozhu Dong, Kotagiri Ramamohanarao:
  Instance-Based Classification by Emerging Patterns. 191-200
  
• Gautam Das, Heikki Mannila:
  Context-Based Similarity Measures for Categorical Databases. 201-210
  
• Ngoc Binh Nguyen, Tu Bao Ho:
  A Mixed Similarity Measure in Near-Linear Computational Complexity for Distance-Based Methods. 211-220
  
• Stéphane Lallich, Ricco Rakotomalala:
  Fast Feature Selection Using Partial Correlation for Multi-vaslued Attributes. 221-231
  

Session 4A - Clustering and Classification

• Markus M. Breunig, Hans-Peter Kriegel, Jörg Sander:
  Fast Hierarchical Clustering Based on Compressed Data and OPTICS. 232-242
  
• Bin Zhang, Meichun Hsu, George Forman:
  Accurate Recasting of Parameter Estimation Algorithms Using Sufficient Statistics for Efficient Parallel Speed-Up: Demonstrated for Center-Based Data Clustering Algorithms. 243-254
  
• Ljupco Todorovski, Peter A. Flach, Nada Lavrac:
  Predictive Performance of Weghted Relative Accuracy. 255-264
  
• Maria Halkidi, Michalis Vazirgiannis, Yannis Batistakis:
  Quality Scheme Assessment in the Clustering Process. 265-276
  

Session 5A - Time Series

• Iztok Savnik, Georg Lausen, Hans-Peter Kahle, Heinrich Spiecker, Sebastian Hein:
  Algorithm for Matching Sets of Time Series. 277-288
  
• Georg Lausen, Iztok Savnik, Aldar Dougarjapov:
  MSTS: A System for Mining Sets of Time Series. 289-298
  
• Juan J. Rodríguez Diez, Carlos Alonso González, Henrik Boström:
  Learning First Order Logic Time Series Classifiers: Rules and Boosting. 299-308
  

Posters

• Silvia Acid, Luis M. de Campos:
  Learning Right Sized Belief Networks by Means of a Hybrid Methodology. 309-315
  
• Brock Barber, Howard J. Hamilton:
  Algorithms for Mining Share Frequent Itemsets Containing Infrequent Subsets. 316-324
  
• Hilan Bensusan, Christophe G. Giraud-Carrier:
  Discovering Task Neighbourhoods Through Landmark Learning Performances. 325-330
  
• Leon Bobrowski, Marek Kretowski:
  Induction of Multivariate Decision Trees by Using Dipolar Criteria. 331-336
  
• Sam Brewer, Tom Khabaza:
  Inductive Logic Programming in Clementine. 337-344
  
• Deborah R. Carvalho, Alex Alves Freitas:
  A Genetic Algorithm-Based Solution for the Problem of Small Disjuncts. 345-352
  
• Antonio Ciampi, Yves Lechevallier:
  Clustering Large, Multi-level Data Sets: An Apporach Based on Kohonen Self Organizing Maps. 353-358
  
• Antonio Ciampi, Djamel A. Zighed, Jérémy Clech:
  Trees and Induction Graphs for Multivariate Response. 359-366
  
• Richard J. Cole II, Peter W. Eklund, Gerd Stumme:
  CEM-Visualisation and Discovery in Email. 367-374
  
• Chabane Djeraba:
  Image Access and Data Mining: An Approach. 375-380
  
• Nikos Drossos, Athanassios Papagelis, Dimitrios Kalles:
  Decision Tree Toolkit: A Component-Based Library of Decision Tree Algorithms. 381-387
  
• Laurent Dury, Laurence Leherte, Daniel P. Vercauteren:
  Determination of Screening Descriptors for Chemical Reaction Databases. 388-394
  
• A. J. Feelders:
  Prior Knowledge in Economic Applications of Data Mining. 395-400
  
• Pierre Geurts, Louis Wehenkel:
  Temporal Machine Learning for Switching Control. 401-408
  
• David Grosser, Jean Diatta, Noël Conruyt:
  Improving Dissimilarity Functions with Domain Knowledge, Applications with IKBS System. 409-415
  
• Attila Gyenesei:
  Mining Weighted Association Rules for Fuzzy Quantitative Items. 416-423
  
• Eui-Hong Han, George Karypis:
  Centroid-Based Document Classification: Analysis and Experimental Results. 424-431
  
• Robert J. Hilderman, Howard J. Hamilton:
  Applying Objective Interestingness Measures in Data Mining Systems. 432-439
  
• Martin Holena:
  Observational Logic Integrates Data Mining Based on Statistics and Neural Networks. 440-445
  
• Dimitar Hristovski, Saso Dzeroski, Borut Peterlin, Anamarija Rozic-Hristovski:
  Supporting Discovery in Medicine by Association Rule Mining of Bibliographic Databases. 446-451
  
• Hillol Kargupta, Weiyun Huang, Krishnamoorthy Sivakumar, Byung-Hoon Park, Shuren Wang:
  Collective Principal Component Analysis from Distributed, Heterogeneous Data. 452-457
  
• Saori Kawasaki, Ngoc Binh Nguyen, Tu Bao Ho:
  Hierarchical Document Clustering Based on Tolerance Rough Set Model. 458-463
  
• Jörg Keller, Valerij Bauer, Wojciech Kwedlo:
  Application of Data-Mining and Knowledge Discovery in Automotive Data Engineering. 464-469
  
• Henryk Jan Komorowski, Torgeir R. Hvidsten, Tor-Kristian Jenssen, Dyre Tjeldvoll, Eivind Hovig, Arne K. Sandvik, Astrid Lægreid:
  Towards Knowledge Discovery from cDNA Microarray Gene Expression Data. 470-475
  
• Marzena Kryszkiewicz:
  Mining with Cover and Extension Operators. 476-482
  
• Pascale Kuntz, Fabrice Guillet, Rémi Lehn, Henri Briand:
  A User-Driven Process for Mining Association Rules. 483-489
  
• Carsten Lanquillon:
  Learning from Labeled and Unlabeled Documents: A Comparative Study on Semi-Supervised Text Classification. 490-497
  
• Pierre-Alain Laur, Florent Masseglia, Pascal Poncelet:
  Schema Mining: Finding Structural Regularity among Semistructured Data. 498-503
  
• Bing Liu, Yiming Ma, Ching Kian Wong:
  Improving an Association Rule Based Classifier. 504-509
  
• Chung-Leung Lui, Korris Fu-Lai Chung:
  Discovery of Generalized Association Rules with Multiple Minimum Supports. 510-515
  
• Adele H. Marshall, Sally I. McClean, Mary Shapcott, Peter H. Millard:
  Learning Dynamic Bayesian Belief Networks Using Conditional Phase-Type Distributions. 516-523
  
• José Francisco Martínez Trinidad, Miriam Velasco-Sánchez, Edgar E. Contreras-Aravelo:
  Discovering Differences in Patients with Uveitis Through Typical Testors by Class. 524-529
  
• Florent Masseglia, Pascal Poncelet, Maguelonne Teisseire:
  Web Usage Mining: How to Efficiently Manage New Transactions and New Clients. 530-535
  
• Frédéric Moal, Teddy Turmeaux, Christel Vrain:
  Mining Relational Databases. 536-541
  
• Maybin K. Muyeba, John A. Keane:
  Interestingness in Attribute-Oriented Induction (AOI): Multiple-Level Rule Generation. 542-549
  
• Takashi Okada, Mayumi Oyama:
  Discovery of Characteristic subgraph Patterns Using Relative Indexing and the Cascade Model. 550-557
  
• Gerhard Paass, Jörg Kindermann:
  Transparency and Predicive Power: Explaining Complex Classification Models. 558-565
  
• Srinivasan Parthasarathy, Mitsunori Ogihara:
  Clustering Distributed Homogeneous Datasets. 566-574
  
• Petra Perner, Chidanand Apté:
  Empirical Evaluation of Feature Subset Selection Based on a Real-World Data Set. 575-580
  
• Gérard Ramstein, Pascal Bunelle, Yannick Jacques:
  Discovery of Ambiguous Patterns in Sequences: Application to Bioinformatics. 581-586
  
• Zbigniew W. Ras, Alicja Wieczorkowska:
  Action-Rules: How to Increase Profit of a Company. 587-592
  
• Gilbert Ritschard, Nicolas Nicoloyannis:
  Aggregation and Association in Cross Tables. 593-598
  
• Céline Robardet, Fabien Feschet, Nicolas Nicoloyannis:
  An Experimental Study of Partition Quality Indices in Clustering. 599-604
  
• Fabrice Rossi, Frédérick Vautrain:
  Expert Constrained Clustering: A Symbolic Approach. 605-612
  
• Ansaf Salleb, Christel Vrain:
  An Application of Association Rules Discovery to Geographic Information Systems. 613-618
  
• Dan A. Simovici, Dana Cristofor, Laurentiu Cristofor:
  Generalized Entropy and Projection Clustering of Categorical Data. 619-625
  
• Vojtech Svátek, Martin Kavalec:
  Supporting Case Acquisition and Labelling in the Cotext of Web Mining. 626-631
  
• Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava:
  Indirect Association: Mining Higher Order Dependencies in Data. 632-637
  
• Tudor Teusan, Gilles Nachouki, Henri Briand, Jacques Philippe:
  Discovering Association Rules in Large, Dense Databases. 638-645
  
• Peter Tselios, Agapios Platis, George A. Vouros:
  Providing Advice to Website Designers Towards Effective Websites Re-Organization. 646-651
  
• Shusaku Tsumoto:
  Clinical Knowledge Discovery in Hospital Information Systems: Two Case Studies. 652-656
  
• Stijn Viaene, Bart Baesens, Tony Van Gestel, Johan A. K. Suykens, Dirk Van den Poel, Jan Vanthienen, Bart De Moor, Guido Dedene:
  Knowledge Discovery Using Least Squares Support Vector Machine Classifiers: A Direct Marketing Case. 657-664
  
• Sholom M. Weiss, Brian F. White, Chidanand Apté:
  Leightweight Document Clustering. 665-672
  
• Hsin-Chang Yang, Chung-Hong Lee:
  Automatic Category Structure Generation and Categorization of Chinese Text Documents. 673-678
  
• Show-Jane Yen:
  Mining Generalized Multiple-Level Association Rules. 679-684
  
• Show-Jane Yen, Chung-Wen Cho:
  An Efficient Approach to Discovering Sequential Patterns in Large Databases. 685-690
  
• Ning Zhong, Juzhen Dong, Setsuo Ohsuga:
  Using Background Knowledge as a Bias to Control the Rule Discovery Process. 691-698
  

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