Discovery Science: 12th... | Buy

This book constitutes the refereed proceedings of the twelfth International Conference, on Discovery Science, DS 2009, held in Porto, Portugal, in October 2009.The 35 revised full papers presented were carefully selected from 92 papers. The scope of the conference includes the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, as well as their applications.

Inference and Learning in Planning (Extended Abstract)	p. 1
Mining Heterogeneous Information Networks by Exploring the Power of Links	p. 13
Learning on the Web	p. 31
Learning and Domain Adaptation	p. 32
The Two Faces of Active Learning	p. 35
An Iterative Learning Algorithm for within-Network Regression in the Transductive Setting	p. 36
Detecting New Kinds of Patient Safety Incidents	p. 51
Using Data Mining for Wine Quality Assessment	p. 66
MICCLLR: Multiple-Instance Learning Using Class Conditional Log Likelihood Ratio	p. 80
On the Complexity of Constraint-Based Theory Extraction	p. 92
Algorithm and Feature Selection for VegOut: A Vegetation Condition Prediction Tool	p. 107
Regression Trees from Data Streams with Drift Detection	p. 121
Mining Frequent Bipartite Episode from Event Sequences	p. 136
Chronicle: A Two-Stage Density-Based Clustering Algorithm for Dynamic Networks	p. 152
Learning Large Margin First Order Decision Lists for Multi-class Classification	p. 168
Ceutrality Measures from Complex Networks in Active Learning	p. 184
Player Modeling for Intelligent Difficulty Adjustment	p. 197
	p. 212
Discovering the Structures of Open Source Programs from Their Developer Mailing Lists	p. 227
A Comparison of Community Detection Algorithms on Artificial Networks	p. 242
Towards an Ontology of Data Mining Investigations	p. 257
OMFP: An Approach for Online Mass Flow Prediction in CFB Boilers	p. 272
C-DenStream: Using Domain Knowledge on a Data Stream	p. 287
Discovering Influential Nodes for SIS Models in Social Networks	p. 302
An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules	p. 317
Precision and Recall for Regression	p. 332
Mining Local Correlation Patterns in Sets of Sequences	p. 347
Subspace Discovery for Promotion: A Cell Clustering Approach	p. 362
Contrasting Sequence Groups by Emerging Sequences	p. 377
A Sliding Window Algorithm for Relational Frequent Patterns Mining from Data Streams	p. 385
A Hybrid Collaborative Filtering System for Contextual Recommendations in Social Networks	p. 393
Linear Programming Boosting by Column and Row Generation	p. 401
Discovering Abstract Concepts to Aid Cross-Map Transfer for a Learning Agent	p. 409
A Dialectic Approach to Problem-Solving	p. 417
Gene Functional Annotation with Dynamic Hierarchical Classification Guided by Orthologs	p. 425
Stream Clustering of Growing Objects	p. 433
Finding the k-Most Abnormal Subgraphs from a Single Graph	p. 441
Latent Topic Extraction from Relational Table for Record Matching	p. 449
Computing a Comprehensible Model for Spam Filtering	p. 457
Better Decomposition Heuristics for the Maximum-Weight Connected Graph Problem Using Betweenness Centrality	p. 465
Author Index	p. 473
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