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...
At present, the search for specific information on the World Wide Web is faced with several problems, which arise on the one hand from the vast number of information sources avail...
Thomas Eiter, Michael Fink, Giuliana Sabbatini, Ha...
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...
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...