Advances in Data Mining: Applications in Image Mining, Medicine and Biotechnology, Management and Environmental Control, and Telecommunications; 4th Industrial Conference on Data Mining, ICDM 2004, Le

ISBN-13: 9783540240549 / Angielski / Miękka / 2004 / 176 str.

Petra Perner

Opis

This book constitutes the thoroughly refereed post-proceedings of the 4th Industrial Conference on Data Mining, ICDM 2004, held in Leipzig, Germany on July 2004.

The conference was focused on advanced data mining applications in image mining, medicine and bioinformatics, management and environmental control, and telecommunications. The 18 revised full papers presented were carefully selected during two rounds of reviewing and improvement. The papers are organized in topical sections on case-based reasoning, image mining, applications in process control and insurance, clustering and association rules, telecomunications, and medicine and biotechnology.

Spis treści

Case-Based Reasoning.- Neuro-symbolic System for Business Internal Control.- Applying Case Based Reasoning Approach in Analyzing Organizational Change Management Data.- Improving the K-NN Classification with the Euclidean Distance Through Linear Data Transformations.- An IBR System to Quantify the Ocean’s Carbon Dioxide Budget.- A Beta-Cooperative CBR System for Constructing a Business Management Model.- Image Mining.- Braving the Semantic Gap: Mapping Visual Concepts from Images and Videos.- Mining Images to Find General Forms of Biological Objects.- Applications in Process Control and Insurance.- The Main Steps to Data Quality.- Cost-Sensitive Design of Claim Fraud Screens.- An Early Warning System for Vehicle Related Quality Data.- Clustering and Association Rules.- Shape-Invariant Cluster Validity Indices.- Mining Indirect Association Rules.- An Association Mining Method for Time Series and Its Application in the Stock Prices of TFT-LCD Industry.- Clustering of Web Sessions Using Levenshtein Metric.- Telecommunication.- A Data Mining Approach for Call Admission Control and Resource Reservation in Wireless Mobile Networks.- Mining of an Alarm Log to Improve the Discovery of Frequent Patterns.- Medicine and Biotechnology.- Feature Selection and Classification Model Construction on Type 2 Diabetic Patient’s Data.- Knowledge Based Phylogenetic Classification Mining.