10. PKDD 2006: Berlin, Germany

Invited Talks

• Charu C. Aggarwal:
  On Temporal Evolution in Data Streams. 1
  
• C. Lee Giles:
  The Future of CiteSeer: CiteSeer^x. 2
  
• Jonathan Schaeffer:
  Learning to Have Fun. 3
  
• Sebastian Thrun:
  Winning the DARPA Grand Challenge. 4
  
• Henry Tirri:
  Challenges of Urban Sensing. 5
  

Long Papers

• Martin Atzmüller, Frank Puppe:
  SD-Map - A Fast Algorithm for Exhaustive Subgroup Discovery. 6-17
  
• Hendrik Blockeel, Leander Schietgat, Jan Struyf, Saso Dzeroski, Amanda Clare:
  Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics. 18-29
  
• Levent Bolelli, Seyda Ertekin, C. Lee Giles:
  Clustering Scientific Literature Using Sparse Citation Graph Analysis. 30-41
  
• Bouchra Bouqata, Christopher D. Carothers, Boleslaw K. Szymanski, Mohammed Javeed Zaki:
  VOGUE: A Novel Variable Order-Gap State Machine for Modeling Sequences. 42-54
  
• Björn Bringmann, Albrecht Zimmermann, Luc De Raedt, Siegfried Nijssen:
  Don't Be Afraid of Simpler Patterns. 55-66
  
• Gladys Castillo, João Gama:
  An Adaptive Prequential Learning Framework for Bayesian Network Classifiers. 67-78
  
• Nicolas Cebron, Michael R. Berthold:
  Adaptive Active Classification of Cell Assay Images. 79-90
  
• Soumen Chakrabarti, Alekh Agarwal:
  Learning Parameters in Entity Relationship Graphs from Ranking Preferences. 91-102
  
• Duen Horng Chau, Shashank Pandit, Christos Faloutsos:
  Detecting Fraudulent Personalities in Networks of Online Auctioneers. 103-114
  
• Ian Davidson, Kiri Wagstaff, Sugato Basu:
  Measuring Constraint-Set Utility for Partitional Clustering Algorithms. 115-126
  
• Christoph F. Eick, Banafsheh Vaezian, Dan Jiang, Jing Wang:
  Discovery of Interesting Regions in Spatial Data Sets Using Supervised Clustering. 127-138
  
• Johannes Fischer, Volker Heun, Stefan Kramer:
  Optimal String Mining Under Frequency Constraints. 139-150
  
• Arik Friedman, Assaf Schuster, Ran Wolff:
  k-Anonymous Decision Tree Induction. 151-162
  
• Gemma C. Garriga, Petra Kralj, Nada Lavrac:
  Closed Sets for Labeled Data. 163-174
  
• Hannes Heikinheimo, Heikki Mannila, Jouni K. Seppänen:
  Finding Trees from Unordered 0-1 Data. 175-186
  
• Jiayuan Huang, Tingshao Zhu, Dale Schuurmans:
  Web Communities Identification from Random Walks. 187-198
  
• Jiayuan Huang, Tingshao Zhu, Russell Greiner, Dengyong Zhou, Dale Schuurmans:
  Information Marginalization on Subgraphs. 199-210
  
• Tsuyoshi Idé:
  Why Does Subsequence Time-Series Clustering Produce Sine Waves? 211-222
  
• Georgiana Ifrim, Gerhard Weikum:
  Transductive Learning for Text Classification Using Explicit Knowledge Models. 223-234
  
• Takahiko Ito, Masashi Shimbo, Daichi Mochihashi, Yuji Matsumoto:
  Exploring Multiple Communities with Kernel-Based Link Analysis. 235-246
  
• Alípio Mário Jorge, Paulo J. Azevedo, Fernando Pereira:
  Distribution Rules with Numeric Attributes of Interest. 247-258
  
• Masahiro Kimura, Kazumi Saito:
  Tractable Models for Information Diffusion in Social Networks. 259-271
  
• Chi-Hoon Lee, Russell Greiner, Osmar R. Zaïane:
  Efficient Spatial Classification Using Decoupled Conditional Random Fields. 272-283
  
• Jessica Lin, Eamonn J. Keogh:
  Group SAX: Extending the Notion of Contrast Sets to Time Series and Multimedia Data. 284-296
  
• Kun Liu, Chris Giannella, Hillol Kargupta:
  An Attacker's View of Distance Preserving Maps for Privacy Preserving Data Mining. 297-308
  
• Ying Liu, Alok N. Choudhary, Jianhong Zhou, Ashfaq A. Khokhar:
  A Scalable Distributed Stream Mining System for Highway Traffic Data. 309-321
  
• Panagis Magdalinos, Christos Doulkeridis, Michalis Vazirgiannis:
  K-Landmarks: Distributed Dimensionality Reduction for Clustering Quality Maintenance. 322-334
  
• Pauli Miettinen, Taneli Mielikäinen, Aristides Gionis, Gautam Das, Heikki Mannila:
  The Discrete Basis Problem. 335-346
  
• Alec Pawling, Nitesh V. Chawla, Amitabh Chaudhary:
  Evaluation of Summarization Schemes for Learning in Streams. 347-358
  
• Marko Salmenkivi:
  Efficient Mining of Correlation Patterns in Spatial Point Data. 359-370
  
• Duygu Ucar, Sitaram Asur, Ümit V. Çatalyürek, Srinivasan Parthasarathy:
  Improving Functional Modularity in Protein-Protein Interactions Graphs Using Hub-Induced Subgraphs. 371-382
  
• Celine Vens, Jan Ramon, Hendrik Blockeel:
  Refining Aggregate Conditions in Relational Learning. 383-394
  
• Herna L. Viktor, Eric Paquet, Hongyu Guo:
  Measuring to Fit: Virtual Tailoring Through Cluster Analysis and Classification. 395-406
  
• Michail Vlachos, Spiros Papadimitriou, Zografoula Vagena, Philip S. Yu:
  RIVA: Indexing and Visualization of High-Dimensional Data Via Dimension Reorderings. 407-420
  
• Michael Wurst, Martin Scholz:
  Distributed Subgroup Mining. 421-433
  
• Ziming Zhuang, Silviu Cucerzan, C. Lee Giles:
  Network Flow for Collaborative Ranking. 434-445
  

Short Papers

• Elke Achtert, Christian Böhm, Hans-Peter Kriegel, Peer Kröger, Ina Müller-Gorman, Arthur Zimek:
  Finding Hierarchies of Subspace Clusters. 446-453
  
• Toon Calders, Bart Goethals, Adriana Prado:
  Integrating Pattern Mining in Relational Databases. 454-461
  
• Joe Catalano, Tom Armstrong, Tim Oates:
  Discovering Patterns in Real-Valued Time Series. 462-469
  
• Giorgio Corani, Chris Edgar, Isabelle Marshall, Keith Wesnes, Marco Zaffalon:
  Classification of Dementia Types from Cognitive Profiles Data. 470-477
  
• Ian Davidson, Wei Fan:
  When Efficient Model Averaging Out-Performs Boosting and Bagging. 478-486
  
• Nele Dexters, Paul W. Purdom, Dirk Van Gucht:
  Peak-Jumping Frequent Itemset Mining Algorithms. 487-494
  
• Khalid El-Arini, Andrew W. Moore, Ting Liu:
  Autonomous Visualization. 495-502
  
• Eibe Frank, Remco R. Bouckaert:
  Naive Bayes for Text Classification with Unbalanced Classes. 503-510
  
• Amol Ghoting, Srinivasan Parthasarathy:
  Knowledge-Conscious Data Clustering. 511-519
  
• Songtao Guo, Xintao Wu, Yingjiu Li:
  On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining. 520-527
  
• Attila Gyenesei, Ralph Schlapbach, Etzard Stolte, Ulrich Wagner:
  Frequent Pattern Discovery Without Binarization: Mining Attribute Profiles. 528-535
  
• Jian Huang, Seyda Ertekin, C. Lee Giles:
  Efficient Name Disambiguation for Large-Scale Databases. 536-544
  
• Bernard Hugueney:
  Adaptive Segmentation-Based Symbolic Representations of Time Series for Better Modeling and Lower Bounding Distance Measures. 545-552
  
• Rezarta Islamaj Dogan, Lise Getoor, W. John Wilbur:
  A Feature Generation Algorithm for Sequences with Application to Splice-Site Prediction. 553-560
  
• Tao Jiang, Ah-Hwee Tan:
  Discovering Image-Text Associations for Cross-Media Web Information Fusion. 561-568
  
• Steffen Kempe, Jochen Hipp:
  Mining Sequences of Temporal Intervals. 569-576
  
• Arno J. Knobbe, Eric K. Y. Ho:
  Pattern Teams. 577-584
  
• Matthijs van Leeuwen, Jilles Vreeken, Arno Siebes:
  Compression Picks Item Sets That Matter. 585-592
  
• Xin Li, Bing Liu, Philip S. Yu:
  Discovering Overlapping Communities of Named Entities. 593-600
  
• Juho Muhonen, Hannu Toivonen:
  Closed Non-derivable Itemsets. 601-608
  
• Satoshi Oyama, Katsumi Tanaka:
  Learning a Distance Metric for Object Identification Without Human Supervision. 609-616
  
• Ricardo Silva, Richard Scheines:
  Towards Association Rules with Hidden Variables. 617-624
  
• Christian Manuel Strobel, Tomas Hrycej:
  A Data Mining Approach to the Joint Evaluation of Field and Manufacturing Data in Automotive Industry. 625-632
  
• Arun C. Surendran, Suvrit Sra:
  Incremental Aspect Models for Mining Document Streams. 633-640
  
• Chao Wang, Srinivasan Parthasarathy:
  Learning Approximate MRFs from Large Transaction Data. 641-649
  
• Karina Wolfram, Andrea Porzel, Alexander Hinneburg:
  Similarity Search for Multi-dimensional NMR-Spectra of Natural Products. 650-658
  

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