Next Generation of Data Mining

by Kargupta; Hillol

• ISBN13: 9781420085860
• ISBN10: 1420085867
• Edition: 1st
• Format: Hardcover
• Copyright: 2008-12-24
• Publisher: Chapman & Hall/

Summary

Drawn from the US National Science Foundation's Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation (NGDM 07), Next Generation of Data Miningexplores emerging technologies  and applications in data mining as well as potential challenges faced by the field.Gathering perspectives from top experts across different disciplines, the book debates upcoming challenges and outlines computational methods. The contributors look at how ecology, astronomy, social science, medicine, finance, and more can benefit from the next generation of data mining techniques. They examine the algorithms, middleware, infrastructure, and privacy policies associated with ubiquitous, distributed, and high performance data mining. They also discuss the impact of new technologies, such as the semantic web, on data mining and provide recommendations for privacy-preserving mechanisms.The dramatic increase in the availability of massive, complex data from various sources iscreating computing, storage, communication, and human-computer interaction challenges for data mining. Providing a framework to better understand these fundamental issues, this volume surveys promising approaches to data mining problems that span an array of disciplines.

Table of Contents

Preface	p. xi
Acknowledgments	p. xiii
Editors	p. xv
Contributors	p. xix
Data Mining in e-Science and Engineering	p. 1
Research Challenges for Data Mining in Science and Engineering	p. 3
Detecting Ecosystem Disturbances and Land Cover Change Using Data Mining	p. 29
Efficient Data-Mining Methods Enabling Genome-Wide Computing	p. 49
Mining Frequent Approximate Sequential Patterns	p. 69
Scientific Data Mining in Astronomy	p. 91
Ubiquitous, Distributed, and High Performance Data Mining	p. 115
Thoughts on Human Emotions, Breakthroughs in Communication, and the Next Generation of Data Mining	p. 117
Research Challenges in Ubiquitous Knowledge Discovery	p. 131
High-Performance Distributed Data Mining	p. 151
User-Centered Biological Information Location by Combining User Profiles and Domain Knowledge	p. 171
Issues and Challenges in Learning from Data Streams	p. 209
Service-Oriented Architectures for Distributed and Mobile Knowledge Discovery	p. 223
Discovering Emergent Behavior from Network Packet Data: Lessons from the Angle Project	p. 243
Architecture Conscious Data Mining: Current Progress and Future Outlook	p. 261
The Web, Semantics, and Text Data Mining	p. 281
Web 2.0 Mining: Analyzing Social Media	p. 283
Searching for "Familiar Strangers" on Blogosphere	p. 295
Toward Semantics-Enabled Infrastructure for Knowledge Acquisition from Distributed Data	p. 317
Nonnegative Matrix Factorization for Document Classification	p. 339
Data Mining in Security, Surveillance, and Privacy Protection	p. 357
Is Privacy Still an Issue for Data Mining?	p. 359
Analysis of Social Networks and Group Dynamics from Electronic Communication	p. 377
Challenges for Dynamic Heterogeneous Networks in Observational Sciences	p. 399
Privacy-Preserving Data Analysis on Graphs and Social Networks	p. 419
Medicine, Social Science, Finance, and Spatial Data Mining	p. 439
Risk Mining as New Trends in Hospital Management	p. 441
Challenges for Information Discovery on Electronic Medical Records	p. 471
Market-Based Profile Infrastructure: Giving Back to the User	p. 505
Challenges in Mining Financial Data	p. 527
Spatial and Spatiotemporal Data Mining: Recent Advances	p. 549
Index	p. 585
Table of Contents provided by Ingram. All Rights Reserved.