Knowledge Discovery in Databases: PKDD 2003: 7th European Conference on Principles and Practice of Knowledge Discovery in Databases, Cavtat-Dubrovnik, Croatia, September 22-26, 2003, Proceedings

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Nada Lavrač
Springer Science & Business Media, 2003 M09 11 - 508 pages
The proceedings of ECML/PKDD2003 are published in two volumes: the P- ceedings of the 14th European Conference on Machine Learning (LNAI 2837) and the Proceedings of the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (LNAI 2838). The two conferences were held on September 22–26, 2003 in Cavtat, a small tourist town in the vicinity of Dubrovnik, Croatia. As machine learning and knowledge discovery are two highly related ?elds, theco-locationofbothconferencesisbene?cialforbothresearchcommunities.In Cavtat, ECML and PKDD were co-located for the third time in a row, following the successful co-location of the two European conferences in Freiburg (2001) and Helsinki (2002). The co-location of ECML2003 and PKDD2003 resulted in a joint program for the two conferences, including paper presentations, invited talks, tutorials, and workshops. Out of 332 submitted papers, 40 were accepted for publication in the ECML2003proceedings,and40wereacceptedforpublicationinthePKDD2003 proceedings. All the submitted papers were reviewed by three referees. In ad- tion to submitted papers, the conference program consisted of four invited talks, four tutorials, seven workshops, two tutorials combined with a workshop, and a discovery challenge.

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Contents

Invited Papers
1
Propensity Score Methodology Applied
16
Majority Classification by Means of Association Rules
35
Anticipated Data Reduction in Constrained Pattern Mining
59
Discovering Unbounded Episodes in Sequential Data
83
Improving Prediction of the Minority Class in Boosting
107
Using Belief Networks and Fisher Kernels
120
On Decision Boundaries of Naıve Bayes in Continuous Domains
144
Using Transduction and Multiview Learning to Answer Emails
266
Exploring Fringe Settings of SVMs for Classification
278
Rule Discovery and Probabilistic Modeling for Onomastic Data
291
Symbolic Distance Measurements Based on Characteristic Subspaces
315
Collaborative Filtering Using Restoration Operators
339
Statistical σPartition Clustering over Data Streams
387
Text Categorisation Using Document Profiling
411
BottomUp Learning of Logic Programs for Information Extraction
435

Visualizing Class Probability Estimators
168
An IndiscernibilityBased Clustering Method with Iterative Refinement
192
Explaining Text Clustering Results Using Semantic Structures
217
Ranking Interesting Subspaces for Clustering High Dimensional Data
241
Mining Rules of Multilevel Diagnostic Procedure from Databases
459
Topic Learning from Few Examples
483
Author Index
507
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