Discovery Science

1. Resampling-Based Framework for Estimating Node Centrality of Large Social Network

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

   Pages 228-239

2. Detecting Maximum k-Plex with Iterative Proper ℓ-Plex Search

   • Yoshiaki Okubo, Masanobu Matsudaira, Makoto Haraguchi

   Pages 240-251

3. Exploiting Bhattacharyya Similarity Measure to Diminish User Cold-Start Problem in Sparse Data

   • Bidyut Kr. Patra, Raimo Launonen, Ville Ollikainen, Sukumar Nandi

   Pages 252-263

4. Failure Prediction – An Application in the Railway Industry

   • Pedro Pereira, Rita P. Ribeiro, João Gama

   Pages 264-275

5. Wind Power Forecasting Using Time Series Cluster Analysis

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

   Pages 276-287

6. Feature Selection in Hierarchical Feature Spaces

   • Petar Ristoski, Heiko Paulheim

   Pages 288-300

7. Incorporating Regime Metrics into Latent Variable Dynamic Models to Detect Early-Warning Signals of Functional Changes in Fisheries Ecology

   • Neda Trifonova, Daniel Duplisea, Andrew Kenny, David Maxwell, Allan Tucker

   Pages 301-312

8. An Efficient Algorithm for Enumerating Chordless Cycles and Chordless Paths

   • Takeaki Uno, Hiroko Satoh

   Pages 313-324

9. Algorithm Selection on Data Streams

   • Jan N. van Rijn, Geoffrey Holmes, Bernhard Pfahringer, Joaquin Vanschoren

   Pages 325-336

10. Sparse Coding for Key Node Selection over Networks

    • Ye Xu, Dan Rockmore

    Pages 337-349

11. Variational Dependent Multi-output Gaussian Process Dynamical Systems

    • Jing Zhao, Shiliang Sun

    Pages 350-361

12. Erratum: Categorize, Cluster, and Classify: A 3-C Strategy for Scientific Discovery in the Medical Informatics Platform of the Human Brain Project

    • Tal Galili, Alexis Mitelpunkt, Netta Shachar, Mira Marcus-Kalish, Yoav Benjamini

    Pages E1-E1

13. Back Matter

    PDF

This book constitutes the proceedings of the 17th International Conference on Discovery Science, DS 2014, held in Bled, Slovenia, in October 2014. The 30 full papers included in this volume were carefully reviewed and selected from 62 submissions. The papers cover topics such as: computational scientific discovery; data mining and knowledge discovery; machine learning and statistical methods; computational creativity; mining scientific data; data and knowledge visualization; knowledge discovery from scientific literature; mining text, unstructured and multimedia data; mining structured and relational data; mining temporal and spatial data; mining data streams; network analysis; discovery informatics; discovery and experimental workflows; knowledge capture and scientific ontologies; data and knowledge integration; logic and philosophy of scientific discovery; and applications of computational methods in various scientific domains.

• algorithms
• artificial intelligence
• data mining
• information retrieval
• intelligent data analysis
• knowledge discovery
• machine learning
• machine learning theory
• pattern mining
• recommendation systems
• recommender systems
• algorithm analysis and problem complexity

• Department of Knowledge Technologies, Jožef Stefan Institute, Ljubljana, Slovenia

  Sašo Džeroski, Panče Panov, Dragi Kocev

• Faculty of Administration, University of Ljubljana, Ljubljana, Slovenia

  Ljupčo Todorovski

Policies and ethics