Discovery Science

1. Front Matter

   Pages I-XV

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2. Resolution Transfer in Cancer Classification Based on Amplification Patterns

   • Prem Raj Adhikari, Jaakko Hollmén

   Pages 1-8

3. Very Short-Term Wind Speed Forecasting Using Spatio-Temporal Lazy Learning

   • Annalisa Appice, Sonja Pravilovic, Antonietta Lanza, Donato Malerba

   Pages 9-16

4. Discovery of Parameters for Animation of Midge Swarms

   • Judith Bjorndahl, Ashley Herman, Richard Hamilton, Howard J. Hamilton, Mark Brigham

   Pages 17-24

5. No Sentiment is an Island:

   • Victoria Bobicev, Marina Sokolova

   Pages 25-32

6. Active Learning for Classifying Template Matches in Historical Maps

   • Benedikt Budig, Thomas C. van Dijk

   Pages 33-47

7. An Evaluation of Score Descriptors Combined with Non-linear Models of Expressive Dynamics in Music

   • Carlos Eduardo Cancino Chacón, Maarten Grachten

   Pages 48-62

8. Geo-Coordinated Parallel Coordinates (GCPC): A Case Study of Environmental Data Analysis

   • Maha El Meseery, Orland Hoeber

   Pages 63-77

9. Generalized Shortest Path Kernel on Graphs

   • Linus Hermansson, Fredrik D. Johansson, Osamu Watanabe

   Pages 78-85

10. Ensembles of Extremely Randomized Trees for Multi-target Regression

    • Dragi Kocev, Michelangelo Ceci

    Pages 86-100

11. Clustering-Based Optimised Probabilistic Active Learning (COPAL)

    • Georg Krempl, Tuan Cuong Ha, Myra Spiliopoulou

    Pages 101-115

12. Predictive Analysis on Tracking Emails for Targeted Marketing

    • Xiao Luo, Revanth Nadanasabapathy, A. Nur Zincir-Heywood, Keith Gallant, Janith Peduruge

    Pages 116-130

13. Semi-supervised Learning for Stream Recommender Systems

    • Pawel Matuszyk, Myra Spiliopoulou

    Pages 131-145

14. Detecting Transmembrane Proteins Using Decision Trees

    • Mohammad Hossein Nikravan, Ashwani Kumar, Sandra Zilles

    Pages 146-160

15. Change Point Detection for Information Diffusion Tree

    • Kouzou Ohara, Kazumi Saito, Masahiro Kimura, Hiroshi Motoda

    Pages 161-169

16. Multi-label Classification via Multi-target Regression on Data Streams

    • Aljaž Osojnik, Panče Panov, Sašo Džeroski

    Pages 170-185

17. Periodical Skeletonization for Partially Periodic Pattern Mining

    • Keisuke Otaki, Akihiro Yamamoto

    Pages 186-200

18. Predicting Drugs Adverse Side-Effects Using a Recommender-System

    • Diogo Pinto, Pedro Costa, Rui Camacho, Vítor Santos Costa

    Pages 201-208

19. Dr. Inventor Framework: Extracting Structured Information from Scientific Publications

    • Francesco Ronzano, Horacio Saggion

    Pages 209-220

20. Predicting Protein Function and Protein-Ligand Interaction with the 3D Neighborhood Kernel

    • Leander Schietgat, Thomas Fannes, Jan Ramon

    Pages 221-235

This book constitutes the proceedings of the 17th International Conference on Discovery Science, DS 2015, held in banff, AB, Canada in October 2015. The 16 long and 12 short papers presendted together with 4 invited talks in this volume were carefully reviewed and selected from 44 submissions. The combination of recent advances in the development and analysis of methods for discovering scienti c knowledge, coming from machine learning, data mining, and intelligent data analysis, as well as their application in various scienti c domains, on the one hand, with the algorithmic advances in machine learning theory, on the other hand, makes every instance of this joint event unique and attractive.

• biomedical knowledge discovery
• data mining
• evolving data and models
• machine learning
• Web mining
• active learning
• artificial intelligence
• clustering
• data stream mining
• evolving datastreams
• human computer interaction
• kernel methods
• knowledge discovery
• learning from text
• mining graphs and structures data
• semi-supervised learning
• spatio-temporal data
• stream mining
• SVM
• algorithm analysis and problem complexity

• University of Ottawa, Ottawa, Canada

  Nathalie Japkowicz

• Faculty of Computer Science, Dalhousie University, HALIFAX, Canada

  Stan Matwin

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