Invited Papers

• 
  Paul R. Cohen, Niall M. Adams: Intelligent Data Analysis in the 21st Century. 1-9
• 
  Pablo Jensen: Analyzing the Localization of Retail Stores with Complex Systems Tools. 10-20

Selected Contributions 1 (Long Talks)

• 
  Tamraparni Dasu, Shankar Krishnan, Dongyu Lin, Suresh Venkatasubramanian, Kevin Yi: Change (Detection) You Can Believe in: Finding Distributional Shifts in Data Streams. 21-34
• 
  Sergio Rodrigues de Morais, Alex Aussem: Exploiting Data Missingness in Bayesian Network Modeling. 35-46
• 
  Stephen L. France, J. Douglas Carroll: DEMScale: Large Scale MDS Accounting for a Ridge Operator and Demographic Variables. 47-58
• 
  Martin Hahmann, Peter Benjamin Volk, Frank Rosenthal, Dirk Habich, Wolfgang Lehner: How to Control Clustering Results? Flexible Clustering Aggregation. 59-70
• 
  Frank Höppner, Frank Klawonn: Compensation of Translational Displacement in Time Series Clustering Using Cross Correlation. 71-82
• 
  Dino Ienco, Ruggero G. Pensa, Rosa Meo: Context-Based Distance Learning for Categorical Data Clustering. 83-94
• 
  Eric P. Jiang: Semi-supervised Text Classification Using RBF Networks. 95-106
• 
  Manuel Martín-Merino, Javier De Las Rivas: Improving k-NN for Human Cancer Classification Using the Gene Expression Profiles. 107-118
• 
  Marianne Mueller, Rómer Rosales, Harald Steck, Sriram Krishnan, Bharat Rao, Stefan Kramer: Subgroup Discovery for Test Selection: A Novel Approach and Its Application to Breast Cancer Diagnosis. 119-130
• 
  Costas Panagiotakis, Nikos Pelekis, Ioannis Kopanakis: Trajectory Voting and Classification Based on Spatiotemporal Similarity in Moving Object Databases. 131-142
• 
  Anju G. Parvathy, Bintu G. Vasudevan, Abhishek Kumar, Rajesh Balakrishnan: Leveraging Call Center Logs for Customer Behavior Prediction. 143-154
• 
  Marc Plantevit, Bruno Crémilleux: Condensed Representation of Sequential Patterns According to Frequency-Based Measures. 155-166
• 
  Elena P. Sapozhnikova: ART-Based Neural Networks for Multi-label Classification. 167-177
• 
  Eerika Savia, Kai Puolamäki, Samuel Kaski: Two-Way Grouping by One-Way Topic Models. 178-189
• 
  Emma Steele, Allan Tucker: Selecting and Weighting Data for Building Consensus Gene Regulatory Networks. 190-201
• 
  Grégory Thibault, Alex Aussem, Stéphane Bonnevay: Incremental Bayesian Network Learning for Scalable Feature Selection. 202-212
• 
  Janne Toivola, Jaakko Hollmén: Feature Extraction and Selection from Vibration Measurements for Structural Health Monitoring. 213-224
• 
  Alexander Borisov, George C. Runger, Eugene Tuv, Nuttha Lurponglukana-Strand: Zero-Inflated Boosted Ensembles for Rare Event Counts. 225-236

Selected Contributions 2 (Short Talks)

• 
  Michele Berlingerio, Michele Coscia, Fosca Giannotti: Mining the Temporal Dimension of the Information Propagation. 237-248
• 
  Albert Bifet, Ricard Gavaldà: Adaptive Learning from Evolving Data Streams. 249-260
• 
  James Cain, Steve Counsell, Stephen Swift, Allan Tucker: An Application of Intelligent Data Analysis Techniques to a Large Software Engineering Dataset. 261-272
• 
  Alpha Diallo, Ahlame Douzal Chouakria, Françoise Giroud: Which Distance for the Identification and the Differentiation of Cell-Cycle Expressed Genes?. 273-284
• 
  Claudia Diamantini, Domenico Potena, Emanuele Storti: Ontology-Driven KDD Process Composition. 285-296
• 
  Lisa Di-Jorio, Anne Laurent, Maguelonne Teisseire: Mining Frequent Gradual Itemsets from Large Databases. 297-308
• 
  Frank Eichinger, Klemens Böhm: Selecting Computer Architectures by Means of Control-Flow-Graph Mining. 309-320
• 
  Kenny Gruchalla, Mark Rast, Elizabeth Bradley, John Clyne, Pablo Mininni: Visualization-Driven Structural and Statistical Analysis of Turbulent Flows. 321-332
• 
  Petr Krajca, Vilém Vychodil: Distributed Algorithm for Computing Formal Concepts Using Map-Reduce Framework. 333-344
• 
  Jian Li, Stephen Swift, Xiaohui Liu: Multi-Optimisation Consensus Clustering. 345-356
• 
  Francisco Martínez-Álvarez, Alicia Troncoso Lora, José C. Riquelme: Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences. 357-368
• 
  Nikolay G. Zagoruiko: Measure of Similarity and Compactness in Competitive Space. 369-380
• 
  Kai Puolamäki, Samuel Kaski: Bayesian Solutions to the Label Switching Problem. 381-392
• 
  Laszlo Szathmary, Petko Valtchev, Amedeo Napoli, Robert Godin: Efficient Vertical Mining of Frequent Closures and Generators. 393-404
• 
  Rémon van de Kamp, Ad Feelders, Nicola Barile: Isotonic Classification Trees. 405-416

last updated on Fri May 24 05:06:00 2013 by the dblp team
data released under the ODC-BY 1.0 license
see also our legal information page