
Advances in Knowledge Discovery and Data Mining
10th Pacific-Asia Conference, PAKDD 2006, Singapore, April 9-12, 2006, Proceedings
Springer (Publisher)
Published on 31. March 2006
Book
Paperback/Softback
XXIV, 879 pages
978-3-540-33206-0 (ISBN)
Description
The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is a leading international conference in the area of data mining and knowledge discovery. This year marks the tenth anniversary of the successful annual series of PAKDD conferences held in the Asia Pacific region. It was with pleasure that we hosted PAKDD 2006 in Singapore again, since the inaugural PAKDD conference was held in Singapore in 1997. PAKDD 2006 continues its tradition of providing an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all aspects of KDD data mining, including data cleaning, data warehousing, data mining techniques, knowledge visualization, and data mining applications. This year, we received 501 paper submissions from 38 countries and regions in Asia, Australasia, North America and Europe, of which we accepted 67 (13.4%) papers as regular papers and 33 (6.6%) papers as short papers. The distribution of the accepted papers was as follows: USA (17%), China (16%), Taiwan (10%), Australia (10%), Japan (7%), Korea (7%), Germany (6%), Canada (5%), Hong Kong (3%), Singapore (3%), New Zealand (3%), France (3%), UK (2%), and the rest from various countries in the Asia Pacific region.
More details
Series
Edition
2006 ed.
Language
English
Place of publication
Berlin
Germany
Publishing group
Springer Berlin
Target group
Professional and scholarly
Research
Illustrations
XXIV, 879 p.
Dimensions
Height: 23.5 cm
Width: 15.5 cm
Weight
1347 gr
ISBN-13
978-3-540-33206-0 (9783540332060)
DOI
10.1007/11731139
Schweitzer Classification
Content
Keynote Speech.- Invited Speech.- Classification.- Ensemble Learning.- Ensemble Learning.- Support Vector Machines.- Text and Document Mining.- Web Mining.- Graph and Network Mining.- Association Rule Mining.- Bio-data Mining.- Outlier and Intrusion Detection.- Privacy.- Relational Database.- Multimedia Mining.- Stream Data Mining.- Temporal Data Mining.- Temporal Data Mining.- Innovative Applications.