We consider the problem of combining ranking results from various sources. In the context of the Web, the main applications include building meta-search engines, combining ranking...
Cynthia Dwork, Ravi Kumar, Moni Naor, D. Sivakumar
One of the central issues in learning to rank for information retrieval is to develop algorithms that construct ranking models by directly optimizing evaluation measures used in i...
We propose a selection scheme called Fitness-based Neighbor Selection (FNS) for multimodal optimization. The FNS is aimed for ill-scaled and locally multimodal domain, both found ...
A great deal of recent research has focused on the challenging task of selecting differentially expressed genes from microarray data (`gene selection'). Numerous gene selecti...
This paper presents a transductive approach to learn ranking functions for extractive multi-document summarization. At the first stage, the proposed approach identifies topic th...