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Knowledge Discovery for Business Information Systems : Kluwer International Series in Engineering & Computer Science - Witold Abramowicz

Knowledge Discovery for Business Information Systems

Kluwer International Series in Engineering & Computer Science

By: Witold Abramowicz (Editor), Jozef Zurada (Editor)

Hardcover

Published: 30th November 2000
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Current database technology and computer hardware allow us to gather, store, access, and manipulate massive volumes of raw data in an efficient and inexpensive manner. In addition, the amount of data collected and warehoused in all industries is growing every year at a phenomenal rate. Nevertheless, our ability to discover critical, non-obvious nuggets of useful information in data that could influence or help in the decision making process, is still limited.
Knowledge discovery (KDD) and Data Mining (DM) is a new, multidisciplinary field that focuses on the overall process of information discovery from large volumes of data. The field combines database concepts and theory, machine learning, pattern recognition, statistics, artificial intelligence, uncertainty management, and high-performance computing.
To remain competitive, businesses must apply data mining techniques such as classification, prediction, and clustering using tools such as neural networks, fuzzy logic, and decision trees to facilitate making strategic decisions on a daily basis.
Knowledge Discovery for Business Information Systems contains a collection of 16 high quality articles written by experts in the KDD and DM field from the following countries: Austria, Australia, Bulgaria, Canada, China (Hong Kong), Estonia, Denmark, Germany, Italy, Poland, Singapore and USA.

Preface
Foreword
List of Contributors
Information Filters Supplying Data Warehouses with Benchmarking Information
Parallel Mining of Association Rules
Unsupervised Feature Ranking and Selection
Approaches to Concept Based Exploration of Information Resources
Hybrid Methodology of Knowledge Discovery for Business Information
Fuzzy Linguistic Summaries of Databases for an Efficient Business Data Analysis and Decision Support
Integrating Data Sources Using a Standardized Global Dictionary
Maintenance of Discovered Association Rules
Multidimensional Business Process Analysis with the Process Warehouse
Amalgamation of Statistics and Data Mining Techniques: Explorations in Customer Lifetime Value Modeling
Robust Business Intelligence Solutions
The Role of Granular Information in Knowledge Discovery in Databases
Dealing with Dimensions in Data Warehousing
Enhancing the KDD Process in the Relational Database Mining Framework by Quantitative Evaluation of Association Rules
Speeding up Hypothesis Development
Sequence Mining in Dynamic and Interactive Environments
Investigation of Artificial Neural Networks for Classifying Levels of Financial Distress of Firms: The Case of an Unbalanced Training Sample
Index
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9780792372431
ISBN-10: 0792372433
Series: Kluwer International Series in Engineering & Computer Science
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 432
Published: 30th November 2000
Publisher: SPRINGER VERLAG GMBH
Country of Publication: NL
Dimensions (cm): 23.39 x 15.6  x 2.54
Weight (kg): 0.81