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DATAMINE
1999
108views more  DATAMINE 1999»
13 years 7 months ago
A Survey of Methods for Scaling Up Inductive Algorithms
Abstract. One of the de ning challenges for the KDD research community is to enable inductive learning algorithms to mine very large databases. This paper summarizes, categorizes, ...
Foster J. Provost, Venkateswarlu Kolluri
SDM
2009
SIAM
175views Data Mining» more  SDM 2009»
14 years 4 months ago
Low-Entropy Set Selection.
Most pattern discovery algorithms easily generate very large numbers of patterns, making the results impossible to understand and hard to use. Recently, the problem of instead sel...
Hannes Heikinheimo, Jilles Vreeken, Arno Siebes, H...
ICMCS
2007
IEEE
159views Multimedia» more  ICMCS 2007»
14 years 2 months ago
Multi-Modal Person-Profiles from Broadcast News Video
The need to analyze and index large amounts of video information is becoming more important as the way people consume media continues to change. In recent years, the push to attac...
Charlie K. Dagli, Sharad V. Rao, Thomas S. Huang
PODS
2006
ACM
132views Database» more  PODS 2006»
14 years 7 months ago
Principles of dataspace systems
The most acute information management challenges today stem from organizations relying on a large number of diverse, interrelated data sources, but having no means of managing the...
Alon Y. Halevy, Michael J. Franklin, David Maier
GFKL
2007
Springer
196views Data Mining» more  GFKL 2007»
14 years 1 months ago
Comparison of Recommender System Algorithms Focusing on the New-item and User-bias Problem
Recommender systems are used by an increasing number of e-commerce websites to help the customers to find suitable products from a large database. One of the most popular techniqu...
Stefan Hauger, Karen H. L. Tso, Lars Schmidt-Thiem...