Ng / Kitsuregawa / Li | Advances in Knowledge Discovery and Data Mining | Buch | 978-3-540-33206-0 | sack.de

Buch, Englisch, 879 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1347 g

Reihe: Lecture Notes in Artificial Intelligence

Ng / Kitsuregawa / Li

Advances in Knowledge Discovery and Data Mining

10th Pacific-Asia Conference, PAKDD 2006, Singapore, April 9-12, 2006, Proceedings
1. Auflage 2006
ISBN: 978-3-540-33206-0
Verlag: Springer

10th Pacific-Asia Conference, PAKDD 2006, Singapore, April 9-12, 2006, Proceedings

Buch, Englisch, 879 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 1347 g

Reihe: Lecture Notes in Artificial Intelligence

ISBN: 978-3-540-33206-0
Verlag: Springer


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.
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Zielgruppe


Research

Weitere Infos & Material


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.



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