Machine Learning and Knowledge Discovery in Databases, Part II: European Conference, ECML PKDD 2010, Athens, Greece, September 5-9, 2011, Proceedings, Part II | SpringerLink
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Machine Learning and Knowledge Discovery in Databases, Part II

European Conference, ECML PKDD 2010, Athens, Greece, September 5-9, 2011, Proceedings, Part II

  • Conference proceedings
  • © 2011

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Editors:
  1. Dimitrios Gunopulos

    1. Department of Informatics and Telecommunications, University of Athens, Athens, Greece

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  2. Thomas Hofmann

    1. Google Switzerland GmbH, Zurich, Switzerland

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  3. Donato Malerba

    1. Department of Computer Science, University of Bari “Aldo Moro”, Bari, Italy

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  4. Michalis Vazirgiannis

    1. Deptartment of Informatics, Athens University of Economics and Business, Athens, Greece

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 6912)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

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Conference proceedings info: ECML PKDD 2011.

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About this book

This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011. The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.

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Table of contents (42 papers)

  1. Front Matter

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  2. Regular Papers

    1. Common Substructure Learning of Multiple Graphical Gaussian Models

      • Satoshi Hara, Takashi Washio
      Pages 1-16

    2. Mining Research Topic-Related Influence between Academia and Industry

      • Dan He
      Pages 17-31

    3. Typology of Mixed-Membership Models: Towards a Design Method

      • Gregor Heinrich
      Pages 32-47

    4. ShiftTree: An Interpretable Model-Based Approach for Time Series Classification

      • Balázs Hidasi, Csaba Gáspár-Papanek
      Pages 48-64

    5. Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining

      • Mohd Hanafi Ahmad Hijazi, Chuntao Jiang, Frans Coenen, Yalin Zheng
      Pages 65-80

    6. Online Structure Learning for Markov Logic Networks

      • Tuyen N. Huynh, Raymond J. Mooney
      Pages 81-96

    7. Fourier-Information Duality in the Identity Management Problem

      • Xiaoye Jiang, Jonathan Huang, Leonidas Guibas
      Pages 97-113

    8. Eigenvector Sensitive Feature Selection for Spectral Clustering

      • Yi Jiang, Jiangtao Ren
      Pages 114-129

    9. Restricted Deep Belief Networks for Multi-view Learning

      • Yoonseop Kang, Seungjin Choi
      Pages 130-145

    10. Motion Segmentation by Model-Based Clustering of Incomplete Trajectories

      • Vasileios Karavasilis, Konstantinos Blekas, Christophoros Nikou
      Pages 146-161

    11. PTMSearch: A Greedy Tree Traversal Algorithm for Finding Protein Post-Translational Modifications in Tandem Mass Spectra

      • Attila Kertész-Farkas, Beáta Reiz, Michael P. Myers, Sándor Pongor
      Pages 162-176

    12. Efficient Mining of Top Correlated Patterns Based on Null-Invariant Measures

      • Sangkyum Kim, Marina Barsky, Jiawei Han
      Pages 177-192

    13. Smooth Receiver Operating Characteristics (smROC) Curves

      • William Klement, Peter Flach, Nathalie Japkowicz, Stan Matwin
      Pages 193-208

    14. A Boosting Approach to Multiview Classification with Cooperation

      • Sokol Koço, Cécile Capponi
      Pages 209-228

    15. ARTEMIS: Assessing the Similarity of Event-Interval Sequences

      • Orestis Kostakis, Panagiotis Papapetrou, Jaakko Hollmén
      Pages 229-244

    16. Unifying Guilt-by-Association Approaches: Theorems and Fast Algorithms

      • Danai Koutra, Tai-You Ke, U. Kang, Duen Horng (Polo) Chau, Hsing-Kuo Kenneth Pao, Christos Faloutsos
      Pages 245-260

    17. Online Clustering of High-Dimensional Trajectories under Concept Drift

      • Georg Krempl, Zaigham Faraz Siddiqui, Myra Spiliopoulou
      Pages 261-276

    18. Gaussian Logic for Predictive Classification

      • Ondřej Kuželka, Andrea Szabóová, Matěj Holec, Filip Železný
      Pages 277-292

    19. Toward a Fair Review-Management System

      • Theodoros Lappas, Evimaria Terzi
      Pages 293-309
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Other volumes

  1. Machine Learning and Knowledge Discovery in Databases

  2. Machine Learning and Knowledge Discovery in Databases

  3. Machine Learning and Knowledge Discovery in Databases

Editors and Affiliations

  • Department of Informatics and Telecommunications, University of Athens, Athens, Greece

    Dimitrios Gunopulos

  • Google Switzerland GmbH, Zurich, Switzerland

    Thomas Hofmann

  • Department of Computer Science, University of Bari “Aldo Moro”, Bari, Italy

    Donato Malerba

  • Deptartment of Informatics, Athens University of Economics and Business, Athens, Greece

    Michalis Vazirgiannis

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