Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
Web is the boundless source of information and no one is able to process the vast amount of new documents published on the web every day, even with filtering out the documents the ...
In geometric computer vision, the structure from motion (SfM) problem can be formulated as a optimization problem with a rank constraint. It is well known that the trace norm of a...
This paper studies document ranking under uncertainty. It is tackled in a general situation where the relevance predictions of individual documents have uncertainty, and are depen...
We present a novel passage-based approach to re-ranking documents in an initially retrieved list so as to improve precision at top ranks. While most work on passage-based document...