In this paper, we describe an approach for the automatic medical annotation task of the 2008 CLEF cross-language image retrieval campaign (ImageCLEF). The data comprise 12076 full...
Unlike traditional classification tasks, multilabel classification allows a sample to associate with more than one label. This generalization naturally arises the difficulty in cla...
Classifying objects in computer vision, we are faced with a great many features one can use. This paper argues that diagrammatic representations help to comprehend properties of fe...
This paper addresses the fundamental problem of document classification, and we focus attention on classification problems where the classes are mutually exclusive. In the course ...
In classification tasks, class-modular strategy has been widely used. It has outperformed classical strategy for pattern classification task in many applications [1]. However, in ...
We report a novel possibility for extracting a small subset of a data base which contains all the information necessary to solve a given classification task: using the Support Vec...
Incremental learning is an approach to deal with the classification task when datasets are too large or when new examples can arrive at any time. One possible approach uses concent...
Many data mining applications can benefit from adapting existing classifiers to new data with shifted distributions. In this paper, we present Adaptive Support Vector Machine (Ada...
The classification task is one of the most important problems in the area of data mining. In this paper we propose a new algorithm for addressing this problem. The main idea deriv...
GeoCLEF ran as a regular track for the second time within the Cross Language Evaluation Forum (CLEF) 2007. The purpose of GeoCLEF is to test and evaluate cross-language geographic ...
Thomas Mandl, Fredric C. Gey, Giorgio Maria Di Nun...