Our work is motivated by the problem of ranking hyperlinked documents for a given query. Given an arbitrary directed graph with edge and node labels, we present a new flow-based ...
Static program checking tools can find many serious bugs in software, but due to analysis limitations they also frequently emit false error reports. Such false positives can easi...
Ted Kremenek, Ken Ashcraft, Junfeng Yang, Dawson R...
A general model is proposed for studying ranking problems. We investigate learning methods based on empirical minimization of the natural estimates of the ranking risk. The empiric...
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...
We consider the problem of learning a ranking function, that is a mapping from instances to rankings over a finite number of labels. Our learning method, referred to as ranking by...
Abstract. To fight the problem of information overload in huge information sources like large document repositories, e. g. citeseer, or internet websites you need a selection crit...
Abstract. We present several results related to ranking. We give a general margin-based bound for ranking based on the L∞ covering number of the hypothesis space. Our bound sugge...
The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in mac...
Accurate probability-based ranking of instances is crucial in many real-world data mining applications. KNN (k-nearest neighbor) [1] has been intensively studied as an effective c...
Ranking is necessary for multiplayer online games to provide players with self-complacence and reference for choosing game counterparts. Most existing ranking solutions are tightl...
Li Tang, Jun Li, Jin Zhou, Zhizhi Zhou, Hao Wang, ...