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...
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...
— 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...
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...
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...