Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, Proceedings,

by Buntine, Wray; Grobelnik, Marko; Mladenic, Dunja; Shawe-Taylor, John

• ISBN13: 9783642041792
• ISBN10: 3642041795
• Edition: 1st
• Format: Paperback
• Copyright: 2009-09-01
• Publisher: Springer-Verlag New York Inc

Summary

This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2009, held in Bled, Slovenia, in September 2009.The 106 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 422 paper submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer. The conference intends to provide an international forum for the discussion of the latest high quality research results in all areas related to machine learning and knowledge discovery in databases. The topics addressed are application of machine learning and data mining methods to real-world problems, particularly exploratory research that describes novel learning and mining tasks and applications requiring non-standard techniques.

Table of Contents

Invited Talk (Abstracts)
Theory-Practice Interplay in Machine Learning - Emerging Theoretical Challenges	p. 1
Are We Three Yet?	p. 2
The Growing Semantic Web	p. 3
Privacy in Web Search Query Log Mining	p. 4
Highly Multilingual News Analysis Applications	p. 5
Machine Learning Journal Abstracts
Combining Instance-Based Learning and Logistic Regression for Multilabel Classification	p. 6
On Structured Output Training: Hard Cases and an Efficient Alternative	p. 7
Spares Kernel SVMs via Cutting-Plane Training	p. 8
Hybrid Least-Squares Algorithms for Approximate Policy Evaluation	p. 9
A Self-training Approach to Cost Sensitive Uncertainty Sampling	p. 10
Learning Multi-linear Representations of Distributions for Efficient Inference	p. 11
Cost-Sensitive Learning Based on Bregman Divergences	p. 12
Data Mining and Knowledge Discovery Journal Abstracts
RTG: A Recursive Realistic Graph Generator Using Random Typing	p. 13
Taxonomy-Driven Lumping for Sequence Mining	p. 29
On Subgroup Discovery in Numerical Domains	p. 30
Harnessing the Strengths of Anytime Algorithms for Constant Data streams	p. 31
Identifying the Components	p. 32
Two-Way Analysis of High-Dimensional Collinear Data	p. 33
A Fast Ensemble Pruning Algorithm Based on Pattern Mining Process	p. 34
Regular Papers
Evaluation Measures for Multi-class Subgroup Discovery	p. 35
Empirical Study of Relational Learning Algorithms in the Phase Transition Framework	p. 51
Topic Significance Ranking of LDA Generative Models	p. 67
Communication-Efficient Classification in P2P Network	p. 83
A Generalization of Forward-Backward Algorithm	p. 99
Mining Graph Evolution Rules	p. 115
Parallel subspace Sampling for Particle Filtering in Dynamic Bayesian Networks	p. 131
Adaptive XML Tree Classification on Evolving Data Streams	p. 147
A Condensed Representation of Itemsets for Analyzing Their Evolution over Time	p. 163
Non-redundant Subgroup Discovery Using a Closure System	p. 179
PLSI: The True Fisher Kernel and beyond: IID Processes, Information Matrix and Model Identification in PLSI	p. 195
Semi-supervised Document Clustering with Simultaneous Text Representation and Categorization	p. 211
One Graph Is Worth a Thousand Logs: Uncovering Hidden Structures in Massive System Event Logs	p. 227
Conference Mining via Generalized Topic Modeling	p. 244
Within-Network Classification Using Local Structure Similarity	p. 260
Multi-task Feature Selection Using the Multiple Inclusion Criterioz (MIC)	p. 276
Kernel Polytope Faces Pursuit	p. 290
Soft Margin Trees	p. 302
Feature Weighting Using Margin and Radius Based Error Bound Optimization in SVMs	p. 315
Margin and Radius Based Multiple Kernel Learning	p. 330
Inference and Validation of Networks	p. 344
Binary Decomposition Methods for Multipartite Ranking	p. 359
Leveraging Higher Order Dependencies between Features for Text Classification	p. 375
Syntactic Structural Kernels for Natural Language Interfaces to Databases	p. 391
Active and Semi-supervised Data Domain Description	p. 407
A Matrix Factorization Approach for Integrating Multiple Data Views	p. 423
Transductive Classification via Dual Regularization	p. 439
Stable and Accurate Feature Selection	p. 455
Efficient Sample Reuse in EM-Based Policy Search	p. 469
Applying Electromagnetic Field Theory Concepts to Clustering with Constraints	p. 485
An l1 Regularization Framework for Optimal Rule Combination	p. 501
A Generic Approach to Topic Models	p. 517
Feature Selection by Transfer Learning with Linear Regularized Models	p. 533
Integrating Logical Reasoning and Probabilistic Chain Graphs	p. 548
Max-Margin Weight Learning for Markov Logic Networks	p. 564
Parameter-Free Hierarchical Co-clustering by n-Ary Splits	p. 580
Mining Peculiar Compositions of Frequent Substrings from Sparse Text Data Using Background Texts	p. 596
Minimum Free Energy Principle for Constraint-Based Learning Bayesian Networks	p. 612
Kernel-Based Copula Processes	p. 628
Compositional Models for Reinforcement Learning	p. 644
Feature Selection for Value Function Approximation Using Bayesian Model Selection	p. 660
Learning Preferences with Hidden Common Cause Relations	p. 676
Feature Selection for Density Level-Sets	p. 692
Efficient Multi-start Strategies for Local Search Algorithms	p. 705
Considering Unseen States as Impossible in Factored Reinforcement Learning	p. 721
Relevance Grounding for Planning in Relational Domains	p. 736
Author Index	p. 753
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