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ICPR
2008
IEEE
16 years 7 months ago
Efficient user preference predictions using collaborative filtering
Two major challenges in collaborative filtering are the efficiency of the algorithms and the quality of the recommendations. A variety of machine learning methods have been applie...
C. Lee Giles, Yang Song
BMCBI
2010
183views more  BMCBI 2010»
15 years 6 months ago
Active learning for human protein-protein interaction prediction
Background: Biological processes in cells are carried out by means of protein-protein interactions. Determining whether a pair of proteins interacts by wet-lab experiments is reso...
Thahir P. Mohamed, Jaime G. Carbonell, Madhavi Gan...
PAKDD
2009
ACM
96views Data Mining» more  PAKDD 2009»
16 years 1 months ago
Aggregated Subset Mining
The usual data mining setting uses the full amount of data to derive patterns for different purposes. Taking cues from machine learning techniques, we explore ways to divide the d...
Albrecht Zimmermann, Björn Bringmann
IJCAI
2007
15 years 7 months ago
Managing Domain Knowledge and Multiple Models with Boosting
We present MBoost, a novel extension to AdaBoost that extends boosting to use multiple weak learners explicitly, and provides robustness to learning models that overfit or are po...
Peng Zang, Charles Lee Isbell Jr.
SDM
2009
SIAM
154views Data Mining» more  SDM 2009»
16 years 3 months ago
AMORI: A Metric-Based One Rule Inducer.
The requirements of real-world data mining problems vary extensively. It is plausible to assume that some of these requirements can be expressed as application-specific performan...
Niklas Lavesson, Paul Davidsson