Knowledge Discovery in Databases: PKDD 2006 : 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Berlin, Germany, September 18-22, 2006, Proceedings / edited by Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou.

Format:

Book

Contributor:

Fürnkranz, Johannes, editor.

Scheffer, Tobias, editor.

Spiliopoulou, Myra, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 4213.

Lecture Notes in Artificial Intelligence ; 4213

Language:

English

Subjects (All):

Data structures (Computer science).

Artificial intelligence.

Database management.

Information storage and retrieval.

Mathematical statistics.

Natural language processing (Computer science).

Data Structures and Information Theory.

Artificial Intelligence.

Database Management.

Information Storage and Retrieval.

Probability and Statistics in Computer Science.

Natural Language Processing (NLP).

Local Subjects:

Data Structures and Information Theory.

Artificial Intelligence.

Database Management.

Information Storage and Retrieval.

Probability and Statistics in Computer Science.

Natural Language Processing (NLP).

Physical Description:

1 online resource (XXII, 660 pages).

Edition:

First edition 2006.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2006.

System Details:

text file PDF

Summary:

The two premier annual European conferences in the areas of machine learning anddatamining havebeencollocatedeversincethejointconferenceinFreiburg, Germany,2001. The European Conference on Machine Learning wasestablished 20 years ago, when the ?rst European Working Session on Learning was held in Orsay, France, in 1986. The conference is growing, and is more lively than ever. The European Conference on Principles and Practice of Knowledge Discovery in Databasescelebratesits tenth anniversary;the ?rst PKDD took place in 1997 in Trondheim, Norway. Over the years, the ECML/PKDD series has evolved into one of the largest and most selective international conferences in these areas, the only one that provides a common forum for the two closely related ?elds. In 2006, the 6th collocated ECML/PKDD took place during September 18-22, when the Humboldt-Universität zu Berlin hosted the 17th European Conference on Machine Learning (ECML) and the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD). The successful model of a hierarchical reviewing process that was introduced last year for the ECML/PKDD 2005 in Porto has been taken over in 2006. We nominated 32 Area Chairs, each of them responsible for several closely related research topics. Suitable areas were selected on the basis of the submission s- tistics for ECML/PKDD 2005 to ensure a proper load balance among the Area Chairs. For the ?rst time, a joint Program Committee was nominated for the two conferences, consisting of 280 renowned researchers,mostly proposed by the AreaChairs.

Contents:

Invited Talks

On Temporal Evolution in Data Streams

The Future of CiteSeer: CiteSeerx

Learning to Have Fun

Winning the DARPA Grand Challenge

Challenges of Urban Sensing

Long Papers

SD-Map - A Fast Algorithm for Exhaustive Subgroup Discovery

Decision Trees for Hierarchical Multilabel Classification: A Case Study in Functional Genomics

Clustering Scientific Literature Using Sparse Citation Graph Analysis

VOGUE: A Novel Variable Order-Gap State Machine for Modeling Sequences

Don't Be Afraid of Simpler Patterns

An Adaptive Prequential Learning Framework for Bayesian Network Classifiers

Adaptive Active Classification of Cell Assay Images

Learning Parameters in Entity Relationship Graphs from Ranking Preferences

Detecting Fraudulent Personalities in Networks of Online Auctioneers

Measuring Constraint-Set Utility for Partitional Clustering Algorithms

Discovery of Interesting Regions in Spatial Data Sets Using Supervised Clustering

Optimal String Mining Under Frequency Constraints

k-Anonymous Decision Tree Induction

Closed Sets for Labeled Data

Finding Trees from Unordered 0-1 Data

Web Communities Identification from Random Walks

Information Marginalization on Subgraphs

Why Does Subsequence Time-Series Clustering Produce Sine Waves?

Transductive Learning for Text Classification Using Explicit Knowledge Models

Exploring Multiple Communities with Kernel-Based Link Analysis

Distribution Rules with Numeric Attributes of Interest

Tractable Models for Information Diffusion in Social Networks

Efficient Spatial Classification Using Decoupled Conditional Random Fields

Group SAX: Extending the Notion of Contrast Sets to Time Series and Multimedia Data

An Attacker's View of Distance Preserving Maps for Privacy Preserving Data Mining

A Scalable Distributed Stream Mining System for Highway Traffic Data

K-Landmarks: Distributed Dimensionality Reduction for Clustering Quality Maintenance

The Discrete Basis Problem

Evaluation of Summarization Schemes for Learning in Streams

Efficient Mining of Correlation Patterns in Spatial Point Data

Improving Functional Modularity in Protein-Protein Interactions Graphs Using Hub-Induced Subgraphs

Refining Aggregate Conditions in Relational Learning

Measuring to Fit: Virtual Tailoring Through Cluster Analysis and Classification

RIVA: Indexing and Visualization of High-Dimensional Data Via Dimension Reorderings

Distributed Subgroup Mining

Network Flow for Collaborative Ranking

Short Papers

Finding Hierarchies of Subspace Clusters

Integrating Pattern Mining in Relational Databases

Discovering Patterns in Real-Valued Time Series

Classification of Dementia Types from Cognitive Profiles Data

When Efficient Model Averaging Out-Performs Boosting and Bagging

Peak-Jumping Frequent Itemset Mining Algorithms

Autonomous Visualization

Naive Bayes for Text Classification with Unbalanced Classes

Knowledge-Conscious Data Clustering

On the Lower Bound of Reconstruction Error for Spectral Filtering Based Privacy Preserving Data Mining

Frequent Pattern Discovery Without Binarization: Mining Attribute Profiles

Efficient Name Disambiguation for Large-Scale Databases

Adaptive Segmentation-Based Symbolic Representations of Time Series for Better Modeling and Lower Bounding Distance Measures

A Feature Generation Algorithm for Sequences with Application to Splice-Site Prediction

Discovering Image-Text Associations for Cross-Media Web Information Fusion

Mining Sequences of Temporal Intervals

Pattern Teams

Compression Picks Item Sets That Matter

Discovering Overlapping Communities of Named Entities

Closed Non-derivable Itemsets

Learning a Distance Metric for Object Identification Without Human Supervision

Towards Association Rules with Hidden Variables

A Data Mining Approach to the Joint Evaluation of Field and Manufacturing Data in Automotive Industry

Incremental Aspect Models for Mining Document Streams

Learning Approximate MRFs from Large Transaction Data

Similarity Search for Multi-dimensional NMR-Spectra of Natural Products.

Other Format:

Printed edition:

ISBN:

978-3-540-46048-0

9783540460480

Access Restriction:

Restricted for use by site license.