3. PKDD 1999: Prague, Czech Republic

Time Series

• Eamonn J. Keogh, Michael J. Pazzani:
  Scaling up Dynamic Time Warping to Massive Dataset. 1-11
  
• Zbigniew R. Struzik, Arno Siebes:
  The Haar Wavelet Transform in the Time Series Similarity Paradigm. 12-22
  
• Shusaku Tsumoto:
  Rule Discovery in Large Time-Series Medical Databases. 23-31
  

Applications

• Hendrik Blockeel, Saso Dzeroski, Jasna Grbovic:
  Simultaneous Prediction of Mulriple Chemical Parameters of River Water Quality with TILDE. 32-40
  
• Elisa Bertino, Barbara Catania, Eleonora Caglio:
  Applying Data Mining Techniques to Wafer Manufacturing. 41-50
  
• Silvia Massa, Pier Paolo Puliafito:
  An Application of Data Mining to the Problem of the University Students' Dropout Using Markov Chains. 51-60
  

Taxonomies and Partitions

• Gou Masuda, Rei Yano, Norihiro Sakamoto, Kazuo Ushijima:
  Discovering and Visualizing Attribute Associations Using Bayesian Networks and Their Use in KDD. 61-70
  
• F. A. El-Mouadib, Jacek Koronacki, Jan M. Zytkow:
  Taxonomy Formation by Approximate Equivalence Relations, Revisited. 71-79
  
• Arthur Flexer:
  On the Use of Self-Organizing Maps for Clustering and Visualization. 80-88
  
• Tapio Elomaa, Juho Rousu:
  Speeding Up the Search for Optimal Partitions. 89-97
  

Logic Methods

• Ljupco Todorovski, Saso Dzeroski:
  Experiments in Meta-level Learning with ILP. 98-106
  
• Andrzej Skowron, Hung Son Nguyen:
  Boolean Reasoning Scheme with Some Applications in Data Mining. 107-115
  
• Jirí Ivánek:
  On the Correspondence between Classes of Implicational and Equivalence Quantifiers. 116-124
  
• Fosca Giannotti, Giuseppe Manco:
  Querying Inductive Databases via Logic-Based User-Defined Aggregates. 125-135
  

Distributed and Multirelational Databases

• Ning Zhong, Yiyu Yao, Setsuo Ohsuga:
  Peculiarity Oriented Multi-database Mining. 136-146
  
• Shusaku Tsumoto:
  Knowledge Discovery in Medical Multi-databases: A Rough Set Approach. 147-155
  
• Rónán Páircéir, Sally I. McClean, Bryan W. Scotney:
  Automated Discovery of Rules and Exeptions from Distributed Databases Using Aggregates. 156-164
  

Text Mining and Feature Selection

• Ronen Feldman, Yonatan Aumann, Moshe Fresko, Orly Liphstat, Binyamin Rosenfeld, Yonatan Schler:
  Text Mining via Information Extraction. 165-173
  
• Chris Clifton, Robert Cooley:
  TopCat: Data Mining for Topic Identification in a Text Corpus. 174-183
  
• Marc Sebban, Djamel A. Zighed, S. Di Palma:
  Selection and Statistical Validation of Features and Prototypes. 184-192
  

Rules and Induction

• Thomas Ågotnes, Henryk Jan Komorowski, Terje Løken:
  Taming Large Rule Models in Rough Set Approaches. 193-203
  
• Dmitry Zelenko:
  Optimizing Disjunctive Association Rules. 204-213
  
• Marc Sebban, Richard Nock:
  Contribution of Boosting in Wrapper Models. 214-222
  
• Richard Nock, Marc Sebban, Pascal Jappy:
  Experiments on a Representation-Independent "Top-Down and Prune" Induction Scheme. 223-231
  

Interesting and Unusual

• Robert J. Hilderman, Howard J. Hamilton:
  Heuristic Measures of Interestingness. 232-241
  
• Thomas Wittmann, Johannes Ruhland, Matthias Eichholz:
  Enhancing Rule Interestingness for Neuro-fuzzy Systems. 242-250
  
• Uzi Murad, Gadi Pinkas:
  Unsupervised Profiling for Identifying Superimposed Fraud. 251-261
  
• Markus M. Breunig, Hans-Peter Kriegel, Raymond T. Ng, Jörg Sander:
  OPTICS-OF: Identifying Local Outliers. 262-270
  

Posters

• Érick Alphonse, Céline Rouveirol:
  Selective Propositionalization for Relational Learning. 271-276
  
• Yonatan Aumann, Ronen Feldman, Yaron Ben-Yehuda, David Landau, Orly Liphstat, Yonatan Schler:
  Circle Graphs: New Visualization Tools for Text-Mining. 277-282
  
• Henry Brighton, Chris Mellish:
  On the Consistency of Information Filters for Lazy Learning Algorithms. 283-288
  
• Robert Cattral, Franz Oppacher, Dwight Deugo:
  Using Genetic Algorithms to Evolve a Rule Hierarchy. 289-294
  
• Xiaodong Chen, Ilias Petrounias:
  Mining Temporal Features in Association Rules. 295-300
  
• Filip Coenen, Gilbert Swinnen, Koen Vanhoof, Geert Wets:
  The Improvement of Response Modeling: Combining Rule-Induction and Case-Based Reasoning. 301-308
  
• Richard J. Cole II, Peter W. Eklund:
  Analyzing an Email Collection Using Formal Concept Analysis. 309-315
  
• Piew Datta:
  Bisiness Focused Evaluation Methods: A Case Study. 316-322
  
• Wolfgang Ertel, Manfred Schramm:
  Combining Data and Knowledge by MaxEnt-Optimization of Probability Distributions. 323-328
  
• A. J. Feelders:
  Handling Missing Data in Trees: Surrogate Splits or Statistical Imputation. 329-334
  
• María C. Fernández-Baizán, Ernestina Menasalvas Ruiz, José M. Peña Sánchez, Socorro Millán, Eloina Mesa:
  Rough Dependencies as a Particular Case of Correlation: Application to the Calculation of Approximative Reducts. 335-340
  
• Christina S. Fertig, Alex Alves Freitas, Lucia V. R. Arruda, Celso A. A. Kaestner:
  A Fuzzy Beam-Search Rule Induction Algorithm. 341-347
  
• Zhiwei Fu:
  An Innovative GA-Based Decision Tree Classifier in Large Scale Data Mining. 348-353
  
• Javier Raymundo García-Serrano, José Francisco Martínez Trinidad:
  Extension to C-means Algorithm for the Use of Similarity Functions. 354-359
  
• Claire J. Kennedy, Christophe G. Giraud-Carrier, Douglas W. Bristol:
  Predicting Chemical Carcinogenesis Using Structural Information Only. 360-365
  
• Mikhail V. Kiselev, Sergei M. Ananyan, Sergei B. Arseniev:
  LA - A Clustering Algorithm with an Automated Selection of Attributes, wich is Invariant to Functional Transformations of Coordinates. 366-371
  
• Mika Klemettinen, Heikki Mannila, A. Inkeri Verkamo:
  Association Rule Selection in a Data Mining Environment. 372-377
  
• Arno J. Knobbe, Arno Siebes, Danïel van der Wallen:
  Multi-relational Decision Tree Induction. 378-383
  
• Sergei O. Kuznetsov:
  Learning of Simple Conceptual Graphs from Positive and Negative Examples. 384-391
  
• Wojciech Kwedlo, Marek Kretowski:
  An Evolutionary Algorithm Using Multivariate Discretization for Decision Rule Induction. 392-397
  
• Stéphane Lallich:
  ZigZag, a New Clustering Algorithm to Analyze Categorical Variable Cross-Classification Tables. 398-405
  
• Jinyan Li, Xiuzhen Zhang, Guozhu Dong, Kotagiri Ramamohanarao, Qun Sun:
  Efficient Mining of High Confidience Association Rules without Support Thresholds. 406-411
  
• Churn-Jung Liau, Duen-Ren Liu:
  A Logical Approach to Fuzzy Data Analysis. 412-417
  
• Guido Lindner, Rudi Studer:
  AST: Support for Algorithm Selection with a CBR Approach. 418-423
  
• Stefano Lodi, Luisella Reami, Claudio Sartori:
  Efficient Shared Near Neighbours Clustering of Large Metric Data Sets. 424-429
  
• Stéphane Lopes, Jean-Marc Petit, Farouk Toumani:
  Discovery of "Interesting" Data Dependencies from a Workload of SQL Statements. 430-435
  
• René MacKinney-Romero, Christophe G. Giraud-Carrier:
  Learning from Highly Structured Data by Decomposition. 436-441
  
• Eddy Mayoraz, Miguel Moreira:
  Combinatorial Approach for Data Binarization. 442-447
  
• Maybin K. Muyeba, John A. Keane:
  Extending Attribute-Oriented Induction as a Key-Preserving Data Mining Method. 448-455
  
• Nikolay I. Nikolaev, Hitoshi Iba:
  Automated Discovery of Polynomials by Inductive Genetic Programming. 456-461
  
• Aleksander Øhrn, Henryk Jan Komorowski:
  Diagnosing Acute Appendicitis with Very Simple Classification Rules. 462-467
  
• Takashi Okada:
  Rule Induction in Cascade Model Based on Sum of Squares Decomposition. 468-474
  
• Michal Pechoucek, Olga Stepánková, Petr Miksovský:
  Maintenance of Discovered Knowledge. 476-483
  
• Clara Pizzuti, Domenico Talia, Giorgio Vonella:
  A Divise Initialisation Method for Clustering Algorithms. 484-491
  
• Thorsten Poddig, Claus Huber:
  A Comparison of Model Selection Procedures for Predicting Turning Points in Financial Time Series. 492-497
  
• Lubos Popelínsky, Tomás Pavelek:
  Mining Lemma Disambiguation Rules from Czech Corpora. 498-503
  
• Chris P. Rainsford, John F. Roddick:
  Adding Temporal Semantics to Association Rules. 504-509
  
• Ricco Rakotomalala, Stéphane Lallich, S. Di Palma:
  Studying the Behavior of Generalized Entropy in Induction Trees Using a M-of-N Concept. 510-517
  
• Zbigniew W. Ras:
  Discovering Rules in Information Trees. 518-523
  
• Andreas Rauber, Dieter Merkl:
  Mining Text Archives: Creating Readable Maps to Structure and Describe Document Collections. 524-529
  
• Johannes Ruhland, Thomas Wittmann:
  Neuro-fuzzy Data Mining for Target Group Selection in Retail Banking. 530-535
  
• Alexandr A. Savinov:
  Mining Possibilistic Set-Valued Rules by Generating Prime Disjunctions. 536-541
  
• Andrzej Skowron, Jaroslaw Stepaniuk:
  Towards Discovery of Information Granules. 542-547
  
• Dominik Slezak, Jakub Wroblewski:
  Classification Algorithms Based on Linear Combinations of Features. 548-553
  
• Myra Spiliopoulou:
  Managing Interesting Rules in Sequence Mining. 554-560
  
• Shinsuke Sugaya, Einoshin Suzuki, Shusaku Tsumoto:
  Support Vector Machines for Knowledge Discovery. 561-567
  
• Ilhan Uysal, H. Altay Güvenir:
  Regression by Feature Projections. 568-573
  
• N. Xiong, Lothar Litz:
  Generating Linguistic Fuzzy Rules for Pattern Classification with Genetic Algorithms. 574-579
  

Tutorials

• Jan Mrázek:
  Data Mining for Robust Business Intelligence Solutions. 580-581
  
• Jean-François Boulicaut:
  Query Languages for Knowledge Discovery in Databases. 582-583
  
• Susanne Köhler, Michael Krieger:
  The ESPRIT Project CreditMine and Its Relevance for the Internet Market. 584-585
  
• Petr Hájek, Jan Rauch:
  Logics and Statistics for Association Rules and Beyond Abstract of Tutorial. 586-587
  
• Myra Spiliopoulou:
  Data Mining for the Web. 588-589
  
• Luc De Raedt, Hendrik Blockeel:
  Relational Learning and Inductive Logic Programming Made Easy Abstract of Tutorial. 590
  

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