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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...
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...
SAC
2010
ACM
15 years 3 months ago
A semantic web-based approach for personalizing news
Hermes is an ontology-based framework for building news personalization services. This framework consists of a news classification phase, which classifies the news, a knowledge ...
Kim Schouten, Philip Ruijgrok, Jethro Borsje, Flav...
WSDM
2010
ACM
211views Data Mining» more  WSDM 2010»
15 years 2 months ago
IntervalRank - Isotonic Regression with Listwise and Pairwise Constraints
Ranking a set of retrieved documents according to their relevance to a given query has become a popular problem at the intersection of web search, machine learning, and informatio...
Taesup Moon, Alex Smola, Yi Chang, Zhaohui Zheng