Ranking data, which result from m raters ranking n items, are difficult to visualize due to their discrete algebraic structure, and the computational difficulties associated with t...
Ranking Abstraction Ittai Balaban Computer Science Department, New York University, 251 Mercer St., New York, New York 10012, United States and Amir Pnueli Computer Science Departm...
We study entity ranking on the INEX entity track and propose a simple graph-based ranking approach that enables to combine scores on document and paragraph level. The combined app...
Many ranking models have been proposed in information retrieval, and recently machine learning techniques have also been applied to ranking model construction. Most of the existin...
Xiubo Geng, Tie-Yan Liu, Tao Qin, Andrew Arnold, H...
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
We consider the problem of learning a ranking function that maximizes a generalization of the Wilcoxon-Mann-Whitney statistic on the training data. Relying on an -accurate approxim...
Vikas C. Raykar, Ramani Duraiswami, Balaji Krishna...
Citation analysis helps in evaluating the impact of scientific collections (journals and conferences), publications and scholar authors. In this paper we examine known algorithms ...
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operat...
Feature ranking is a fundamental machine learning task with various applications, including feature selection and decision tree learning. We describe and analyze a new feature ran...
: In this paper we consider the vertex ranking problem of weighted trees. We show that this problem is strongly NP-hard. We also give a polynomial-time reduction from the problem o...