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...
Mashups are situational applications that join multiple sources to better meet the information needs of Web users. Web sources can be huge databases behind query interfaces, which...
Abstract. In this paper, we propose a new method for learning to rank. `Ranking SVM' is a method for performing the task. It formulizes the problem as that of binary classific...
Two popular webpage ranking algorithms are HITS and PageRank. HITS emphasizes mutual reinforcement between authority and hub webpages, while PageRank emphasizes hyperlink weight n...
Chris H. Q. Ding, Xiaofeng He, Parry Husbands, Hon...
In this work, we proposed to use the Zoomed Ranking approach to rank and select time series models. Zoomed Ranking, originally proposed to generate a ranking of candidate algorith...