This paper presents a framework for user-oriented text mining. It is then illustrated with an example of discovering knowledge from competitors’ websites. The knowledge to be di...
Abstract. Association rule algorithms often generate an excessive number of rules, many of which are not significant. It is difficult to determine which rules are more useful, int...
This paper addresses cost-sensitive classification in the setting where there are costs for measuring each attribute as well as costs for misclassification errors. We show how to ...
In this paper we propose a method for selecting an appropriate subset of sensors with a view to minimize estimation error while tracking a target with sensors spread across in a 2...
This paper introduces a choice-based method that for the first time makes it possible to quantitatively measure regret theory, one of the most popular models of decision under unc...