To purchase hard copies of this book, please email:
orders@intechopen.com
Share this page
This book is indexed in
Computer and Information Science » Numerical Analysis and Scientific Computing
New Fundamental Technologies in Data Mining
Edited by Kimito Funatsu, ISBN 978-953-307-547-1, Hard cover, 584 pages, Publisher: InTech, Chapters published January 21, 2011 under CC BY-NC-SA 3.0 license
DOI: 10.5772/563 
The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.
- Chapter 1
Service-Oriented Data Mining - Chapter 2 Database Marketing Process Supported by Ontologies: a Data Mining System Architecture Proposal
- Chapter 3 Parallel and Distributed Data Mining
- Chapter 4 Modeling Information Quality Risk for Data Mining and Case Studies
- Chapter 5 Enabling Real-Time Business Intelligence by Stream Data Mining
- Chapter 6 From the Business Decision Modeling to the Use Case Modeling in Data Mining Projects
- Chapter 7 A Novel Configuration-Driven Data Mining Framework for Health and Usage Monitoring Systems
- Chapter 8 Data Mining in Hospital Information System
- Chapter 9 Data Warehouse and the Deployment of Data Mining Process to Make Decision for Leishmaniasis in Marrakech City
- Chapter 10 Data Mining in Ubiquitous Healthcare
- Chapter 11 Data Mining in Higher Education
- Chapter 12 EverMiner - towards Fully Automated KDD Process
- Chapter 13 A Software Architecture for Data Mining Environment
- Chapter 14 Supervised Learning Classifier System for Grid Data Mining
- Chapter 15 A New Multi-Viewpoint and Multi-Level Clustering Paradigm for Efficient Data Mining Tasks
- Chapter 16 Spatial Clustering Technique for Data Mining
- Chapter 17 The Search for Irregularly Shaped Clusters in Data Mining
- Chapter 18 A General Model for Relational Clustering
- Chapter 19 Classifiers Based on Inverted Distances
- Chapter 20 2D Figure Pattern Mining
- Chapter 21 Quality Model based on Object-oriented Metrics and Naive Bayes
- Chapter 22 Extraction of Embedded Image Segment Data Using Data Mining with Reduced Neurofuzzy Systems
- Chapter 23 On Ranking Discovered Rules of Data Mining by Data Envelopment Analysis: Some Models with Wider Applications
- Chapter 24 Temporal Rules over Time Structures with Different Granularities - a Stochastic Approach
- Chapter 25 Data Mining for Problem Discovery
- Chapter 26 Development of a Classification Rule Mining Framework by Using Temporal Pattern Extraction
- Chapter 27 Evolutionary-Based Classification Technique
- Chapter 28 Multiobjective Design Exploration in Space Engineering
- Chapter 29 Privacy Preserving Data Mining
- Chapter 30 Using Markov Models to Mine Temporal and Spatial Data