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...
Data stream is a newly emerging data model for applications like environment monitoring, Web click stream, network traffic monitoring, etc. It consists of an infinite sequence of d...
K Nearest Neighbor search has many applications including data mining, multi-media, image processing, and monitoring moving objects. In this paper, we study the problem of KNN over...
Wenjie Zhang, Xuemin Lin, Muhammad Aamir Cheema, Y...
Abstract-- This paper introduces a deterministic approximation algorithm with error guarantees for computing the probability of propositional formulas over discrete random variable...
We study the problem of finding frequent items in a continuous stream of itemsets. A new frequency measure is introduced, based on a flexible window length. For a given item, its ...