In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...
In web search, recency ranking refers to ranking documents by relevance which takes freshness into account. In this paper, we propose a retrieval system which automatically detect...
Anlei Dong, Yi Chang, Zhaohui Zheng, Gilad Mishne,...
In this paper a novel ranking-based face recognition (FR) scheme is proposed. Compared with classical twoclass (intra/extra person) and multi-class (each person a single class) sc...
In supervised machine learning, variable ranking aims at sorting the input variables according to their relevance w.r.t. an output variable. In this paper, we propose a new relevan...