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ICML
1998
IEEE
15 years 10 months ago
An Efficient Boosting Algorithm for Combining Preferences
We study the problem of learning to accurately rank a set of objects by combining a given collection of ranking or preference functions. This problem of combining preferences aris...
Yoav Freund, Raj D. Iyer, Robert E. Schapire, Yora...
PODS
2005
ACM
115views Database» more  PODS 2005»
15 years 10 months ago
A divide-and-merge methodology for clustering
We present a divide-and-merge methodology for clustering a set of objects that combines a top-down "divide" phase with a bottom-up "merge" phase. In contrast, ...
David Cheng, Santosh Vempala, Ravi Kannan, Grant W...
CIKM
2009
Springer
15 years 4 months ago
Expected reciprocal rank for graded relevance
While numerous metrics for information retrieval are available in the case of binary relevance, there is only one commonly used metric for graded relevance, namely the Discounted ...
Olivier Chapelle, Donald Metlzer, Ya Zhang, Pierre...
ICC
2007
IEEE
199views Communications» more  ICC 2007»
15 years 4 months ago
7DS - Node Cooperation and Information Exchange in Mostly Disconnected Networks
— When the node density in a network decreases below the level necessary to sustain ad-hoc and mesh networks, communication can succeed only by leveraging node mobility and trans...
Suman Srinivasan, Arezu Moghadam, Se Gi Hong, Henn...
SIGIR
2003
ACM
15 years 3 months ago
Automatic ranking of retrieval systems in imperfect environments
The empirical investigation of the effectiveness of information retrieval (IR) systems requires a test collection, a set of query topics, and a set of relevance judgments made by ...
Rabia Nuray, Fazli Can