Machine Learning and Data Mining in Pattern Recognition : 5th International Conference, MLDM 2007, Leipzig, Germany, July 18-20, 2007, Proceedings / edited by Petra Perner.

Format:

Book

Contributor:

Perner, Petra, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 4571.

Lecture Notes in Artificial Intelligence ; 4571

Language:

English

Subjects (All):

Artificial intelligence.

Logic, Symbolic and mathematical.

Database management.

Data mining.

Pattern perception.

Optical data processing.

Artificial Intelligence.

Mathematical Logic and Formal Languages.

Database Management.

Data Mining and Knowledge Discovery.

Pattern Recognition.

Image Processing and Computer Vision.

Local Subjects:

Artificial Intelligence.

Mathematical Logic and Formal Languages.

Database Management.

Data Mining and Knowledge Discovery.

Pattern Recognition.

Image Processing and Computer Vision.

Physical Description:

1 online resource (XIV, 916 pages).

Edition:

First edition 2007.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2007.

System Details:

text file PDF

Summary:

MLDM / ICDM Medaillie Meissner Porcellan, the "White Gold" of King August the Strongest of Saxonia Gottfried Wilhelm von Leibniz, the great mathematician and son of Leipzig, was watching over us during our event in Machine Learning and Data Mining in Pattern Recognition (MLDM 2007). He can be proud of what we have achieved in this area so far. We had a great research program this year. This was the fifth MLDM in Pattern Recognition event held in Leipzig (www.mldm.de). Today, there are many international meetings carrying the title machine learning and data mining, whose topics are text mining, knowledge discovery, and applications. This meeting from the very first event has focused on aspects of machine learning and data mining in pattern recognition problems. We planned to reorganize classical and well-established pattern recognition paradigms from the view points of machine learning and data mining. Although it was a challenging program in the late 1990s, the idea has provided new starting points in pattern recognition and has influenced other areas such as cognitive computer vision. For this edition, the Program Committee received 258 submissions from 37 countries (see Fig. 1). To handle this high number of papers was a big challenge for the reviewers. Every paper was thoroughly reviewed and all authors received a detailed report on their submitted work.

Contents:

Invited Talk

Data Clustering: User's Dilemma

Classification

On Concentration of Discrete Distributions with Applications to Supervised Learning of Classifiers

Comparison of a Novel Combined ECOC Strategy with Different Multiclass Algorithms Together with Parameter Optimization Methods

Multi-source Data Modelling: Integrating Related Data to Improve Model Performance

An Empirical Comparison of Ideal and Empirical ROC-Based Reject Rules

Outlier Detection with Kernel Density Functions

Generic Probability Density Function Reconstruction for Randomization in Privacy-Preserving Data Mining

An Incremental Fuzzy Decision Tree Classification Method for Mining Data Streams

On the Combination of Locally Optimal Pairwise Classifiers

Feature Selection, Extraction and Dimensionality Reduction

An Agent-Based Approach to the Multiple-Objective Selection of Reference Vectors

On Applying Dimension Reduction for Multi-labeled Problems

Nonlinear Feature Selection by Relevance Feature Vector Machine

Affine Feature Extraction: A Generalization of the Fukunaga-Koontz Transformation

Clustering

A Bounded Index for Cluster Validity

Varying Density Spatial Clustering Based on a Hierarchical Tree

Kernel MDL to Determine the Number of Clusters

Critical Scale for Unsupervised Cluster Discovery

Minimum Information Loss Cluster Analysis for Categorical Data

A Clustering Algorithm Based on Generalized Stars

Support Vector Machine

Evolving Committees of Support Vector Machines

Choosing the Kernel Parameters for the Directed Acyclic Graph Support Vector Machines

Data Selection Using SASH Trees for Support Vector Machines

Dynamic Distance-Based Active Learning with SVM

Transductive Inference

Off-Line Learning with Transductive Confidence Machines: An Empirical Evaluation

Transductive Learning from Relational Data

Association Rule Mining

A Novel Rule Ordering Approach in Classification Association Rule Mining

Distributed and Shared Memory Algorithm for Parallel Mining of Association Rules

Mining Spam, Newsgroups, Blogs

Analyzing the Performance of Spam Filtering Methods When Dimensionality of Input Vector Changes

Blog Mining for the Fortune 500

A Link-Based Rank of Postings in Newsgroup

Intrusion Detection and Networks

A Comparative Study of Unsupervised Machine Learning and Data Mining Techniques for Intrusion Detection

Long Tail Attributes of Knowledge Worker Intranet Interactions

A Case-Based Approach to Anomaly Intrusion Detection

Sensing Attacks in Computers Networks with Hidden Markov Models

Frequent and Common Item Set Mining

FIDS: Monitoring Frequent Items over Distributed Data Streams

Mining Maximal Frequent Itemsets in Data Streams Based on FP-Tree

CCIC: Consistent Common Itemsets Classifier

Mining Marketing Data

Development of an Agreement Metric Based Upon the RAND Index for the Evaluation of Dimensionality Reduction Techniques, with Applications to Mapping Customer Data

A Sequential Hybrid Forecasting System for Demand Prediction

A Unified View of Objective Interestingness Measures

Comparing State-of-the-Art Collaborative Filtering Systems

Structural Data Mining

Reducing the Dimensionality of Vector Space Embeddings of Graphs

PE-PUC: A Graph Based PU-Learning Approach for Text Classification

Efficient Subsequence Matching Using the Longest Common Subsequence with a Dual Match Index

A Direct Measure for the Efficacy of Bayesian Network Structures Learned from Data

Image Mining

A New Combined Fractal Scale Descriptor for Gait Sequence

Palmprint Recognition by Applying Wavelet Subband Representation and Kernel PCA

A Filter-Refinement Scheme for 3D Model Retrieval Based on Sorted Extended Gaussian Image Histogram

Fast-Maneuvering Target Seeking Based on Double-Action Q-Learning

Mining Frequent Trajectories of Moving Objects for Location Prediction

Categorizing Evolved CoreWar Warriors Using EM and Attribute Evaluation

Restricted Sequential Floating Search Applied to Object Selection

Color Reduction Using the Combination of the Kohonen Self-Organized Feature Map and the Gustafson-Kessel Fuzzy Algorithm

A Hybrid Algorithm Based on Evolution Strategies and Instance-Based Learning, Used in Two-Dimensional Fitting of Brightness Profiles in Galaxy Images

Gait Recognition by Applying Multiple Projections and Kernel PCA

Medical, Biological, and Environmental Data Mining

A Machine Learning Approach to Test Data Generation: A Case Study in Evaluation of Gene Finders

Discovering Plausible Explanations of Carcinogenecity in Chemical Compounds

One Lead ECG Based Personal Identification with Feature Subspace Ensembles

Classification of Breast Masses in Mammogram Images Using Ripley's K Function and Support Vector Machine

Selection of Experts for the Design of Multiple Biometric Systems

Multi-agent System Approach to React to Sudden Environmental Changes

Equivalence Learning in Protein Classification

Text and Document Mining

Statistical Identification of Key Phrases for Text Classification

Probabilistic Model for Structured Document Mapping

Application of Fractal Theory for On-Line and Off-Line Farsi Digit Recognition

Hybrid Learning of Ontology Classes

Discovering Relations Among Entities from XML Documents.

Other Format:

Printed edition:

ISBN:

978-3-540-73499-4

9783540734994

Access Restriction:

Restricted for use by site license.