Abstract. An information theoretic framework for grouping observations is proposed. The entropy change incurred by new observations is analyzed using the Kalman filter update equa...
In data mining applications, highly sized contexts are handled what usually results in a considerably large set of frequent itemsets, even for high values of the minimum support t...
Tarek Hamrouni, Sadok Ben Yahia, Engelbert Mephu N...
We present an active learning approach to choose image annotation requests among both object category labels and the objects’ attribute labels. The goal is to solicit those labe...
The main statistics used in rough set data analysis, the approximation quality, is of limited value when there is a choice of competing models for predicting a decision variable. ...
Click data captures many users’ document preferences for a query and has been shown to help significantly improve search engine ranking. However, most click data is noisy and of...