Advances in Intelligent Data Analysis VI : 6th International Symposium on Intelligent Data Analysis, IDA 2005, Madrid, Spain, September 8-10, 2005, Proceedings / edited by A. Fazel Famili, Joost N. Kok, José M. Pena, Arno Siebes, Ad Feelders.

Format:

Book

Contributor:

Famili, A. Fazel, editor.

Kok, Joost N., editor.

Peña, José M., editor.

Siebes, Arno, 1958- editor.

Feelders, Ad, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

LNCS sublibrary. Information systems and applications, incl. Internet/Web, and HCI ; SL 3, 3646.

Information Systems and Applications, incl. Internet/Web, and HCI ; 3646

Language:

English

Subjects (All):

Artificial intelligence.

Information storage and retrieval.

Mathematical statistics.

Pattern perception.

Information technology.

Business--Data processing.

Business.

Artificial Intelligence.

Information Storage and Retrieval.

Probability and Statistics in Computer Science.

Pattern Recognition.

IT in Business.

Local Subjects:

Artificial Intelligence.

Information Storage and Retrieval.

Probability and Statistics in Computer Science.

Pattern Recognition.

IT in Business.

Physical Description:

1 online resource (XIV, 534 pages).

Edition:

First edition 2005.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2005.

System Details:

text file PDF

Summary:

One of the superb characteristics of Intelligent Data Analysis (IDA) is that it is an interdisciplinary ?eld in which researchers and practitioners from a number of areas are involved in a typical project. This also creates a challenge in which the success of a team depends on the participation of users and domain experts who need to interact with researchers and developers of any IDA system. All this is usually re?ected in successful projects and of course on the papers that were evaluated by this year's program committee from which the ?nal program has been developed. In our call for papers, we solicited papers on (i) applications and tools, (ii) theory and general principles, and (iii) algorithms and techniques. We received a total of 184 papers, reviewing these was a major challenge. Each paper was assigned to three reviewers. In the end 46 papers were accepted, which are all included in the proceedings and presented at the conference. This year's papers re?ect the results of applied and theoretical researchfrom a number of disciplines all of which are related to the ?eld of Intelligent Data Analysis. To have the best combination of theoretical and applied research and also provide the best focus, we have divided this year's IDA program into tu- rials, invited talks, panel discussions and technical sessions.

Contents:

Probabilistic Latent Clustering of Device Usage

Condensed Nearest Neighbor Data Domain Description

Balancing Strategies and Class Overlapping

Modeling Conditional Distributions of Continuous Variables in Bayesian Networks

Kernel K-Means for Categorical Data

Using Genetic Algorithms to Improve Accuracy of Economical Indexes Prediction

A Distance-Based Method for Preference Information Retrieval in Paired Comparisons

Knowledge Discovery in the Identification of Differentially Expressed Genes in Tumoricidal Macrophage

Searching for Meaningful Feature Interactions with Backward-Chaining Rule Induction

Exploring Hierarchical Rule Systems in Parallel Coordinates

Bayesian Networks Learning for Gene Expression Datasets

Pulse: Mining Customer Opinions from Free Text

Keystroke Analysis of Different Languages: A Case Study

Combining Bayesian Networks with Higher-Order Data Representations

Removing Statistical Biases in Unsupervised Sequence Learning

Learning from Ambiguously Labeled Examples

Learning Label Preferences: Ranking Error Versus Position Error

FCLib: A Library for Building Data Analysis and Data Discovery Tools

A Knowledge-Based Model for Analyzing GSM Network Performance

Sentiment Classification Using Information Extraction Technique

Extending the SOM Algorithm to Visualize Word Relationships

Towards Automatic and Optimal Filtering Levels for Feature Selection in Text Categorization

Block Clustering of Contingency Table and Mixture Model

Adaptive Classifier Combination for Visual Information Processing Using Data Context-Awareness

Self-poised Ensemble Learning

Discriminative Remote Homology Detection Using Maximal Unique Sequence Matches

From Local Pattern Mining to Relevant Bi-cluster Characterization

Machine-Learning with Cellular Automata

MDS polar : A New Approach for Dimension Reduction to Visualize High Dimensional Data

Miner Ants Colony: A New Approach to Solve a Mine Planning Problem

Extending the GA-EDA Hybrid Algorithm to Study Diversification and Intensification in GAs and EDAs

Spatial Approach to Pose Variations in Face Verification

Analysis of Feature Rankings for Classification

A Mixture Model-Based On-line CEM Algorithm

Reliable Hierarchical Clustering with the Self-organizing Map

Statistical Recognition of Noun Phrases in Unrestricted Text

Successive Restrictions Algorithm in Bayesian Networks

Modelling the Relationship Between Streamflow and Electrical Conductivity in Hollin Creek, Southeastern Australia

Biological Cluster Validity Indices Based on the Gene Ontology

An Evaluation of Filter and Wrapper Methods for Feature Selection in Categorical Clustering

Dealing with Data Corruption in Remote Sensing

Regularized Least-Squares for Parse Ranking

Bayesian Network Classifiers for Time-Series Microarray Data

Feature Discovery in Classification Problems

A New Hybrid NM Method and Particle Swarm Algorithm for Multimodal Function Optimization

Detecting Groups of Anomalously Similar Objects in Large Data Sets.

Other Format:

Printed edition:

ISBN:

978-3-540-31926-9

9783540319269

Access Restriction:

Restricted for use by site license.