We propose a number of techniques for obtaining a global ranking from data that may be incomplete and imbalanced — characteristics that are almost universal to modern datasets co...
We study the problem of producing a global ranking of items given pairwise ranking information, when the items to be ranked arrive in an online fashion. We study both the maximizat...
Abstract. We propose a number of techniques for learning a global ranking from data that may be incomplete and imbalanced -- characteristics that are almost universal to modern dat...
This paper studies global ranking problem by learning to rank methods. Conventional learning to rank methods are usually designed for `local ranking', in the sense that the r...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
Search engines are among the most important applications or services on the web. Most existing successful search engines use global ranking algorithms to generate the ranking of do...
We provide an approach to distribute the calculation of PageRank, by splitting the graph into its strongly connected components. As we prove, the global ranking may be calculated c...