Advances in Intelligent Data Analysis XII

1. Front Matter

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2. Invited Papers

   1. Data, Not Dogma: Big Data, Open Data, and the Opportunities Ahead

      • David J. Hand

      Pages 1-12

   2. Computational Techniques for Crop Disease Monitoring in the Developing World

      • John Quinn

      Pages 13-18

   3. Subjective Interestingness in Exploratory Data Mining

      • Tijl De Bie

      Pages 19-31

3. Selected Contributions

   1. Time Point Estimation of a Single Sample from High Throughput Experiments Based on Time-Resolved Data and Robust Correlation Measures

      • Nada Abidi, Frank Klawonn, Jörg Oliver Thumfart

      Pages 32-43

   2. Detecting Events in Molecular Dynamics Simulations

      • Iris Adä, Michael R. Berthold

      Pages 44-55

   3. Graph Clustering by Maximizing Statistical Association Measures

      • Julien Ah-Pine

      Pages 56-67

   4. Evaluation of Association Rule Quality Measures through Feature Extraction

      • José L. Balcázar, Francis Dogbey

      Pages 68-79

   5. Towards Comprehensive Concept Description Based on Association Rules

      • Petr Berka

      Pages 80-91

   6. CD-MOA: Change Detection Framework for Massive Online Analysis

      • Albert Bifet, Jesse Read, Bernhard Pfahringer, Geoff Holmes, Indrė Žliobaitė

      Pages 92-103

   7. Integrating Multiple Studies of Wheat Microarray Data to Identify Treatment-Specific Regulatory Networks

      • Valeria Bo, Artem Lysenko, Mansoor Saqi, Dimah Habash, Allan Tucker

      Pages 104-115

   8. Finding Frequent Patterns in Parallel Point Processes

      • Christian Borgelt, David Picado-Muiño

      Pages 116-126

   9. Behavioral Clustering for Point Processes

      • Christian Braune, Christian Borgelt, Rudolf Kruse

      Pages 127-137

   10. Estimating Prediction Certainty in Decision Trees

       • Eduardo P. Costa, Sicco Verwer, Hendrik Blockeel

       Pages 138-149

   11. Interactive Discovery of Interesting Subgroup Sets

       • Vladimir Dzyuba, Matthijs van Leeuwen

       Pages 150-161

   12. Gaussian Mixture Models for Time Series Modelling, Forecasting, and Interpolation

       • Emil Eirola, Amaury Lendasse

       Pages 162-173

   13. When Does Active Learning Work?

       • Lewis P. G. Evans, Niall M. Adams, Christoforos Anagnostopoulos

       Pages 174-185

   14. OrderSpan: Mining Closed Partially Ordered Patterns

       • Mickaël Fabrègue, Agnès Braud, Sandra Bringay, Florence Le Ber, Maguelonne Teisseire

       Pages 186-197

   15. Learning Multiple Temporal Matching for Time Series Classification

       • Cedric Frambourg, Ahlame Douzal-Chouakria, Eric Gaussier

       Pages 198-209

   16. On the Importance of Nonlinear Modeling in Computer Performance Prediction

       • Joshua Garland, Elizabeth Bradley

       Pages 210-222

This book constitutes the refereed conference proceedings of the 12th International Conference on Intelligent Data Analysis, which was held in October 2013 in London, UK. The 36 revised full papers together with 3 invited papers were carefully reviewed and selected from 84 submissions handling all kinds of modeling and analysis methods, irrespective of discipline. The papers cover all aspects of intelligent data analysis, including papers on intelligent support for modeling and analyzing data from complex, dynamical systems.

• big data
• genetic algorithms
• large-scale social network analysis
• search engine
• virtual reality
• algorithm analysis and problem complexity

• School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, UK

  Allan Tucker, Stephen Swift

• Faculty of Computer Science/IT, Ostfalia University of Applied Sciences, Wolfenbüttel, Germany

  Frank Höppner

• Faculty of Science, Department of Information and Computing Science, Buys Ballot Laboratory, Universiteit Utrecht, Utrecht, The Netherlands

  Arno Siebes

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