The aim of this paper is to show how abduction can be used in classification tasks when we deal with incomplete data. Some classifiers, even if based on decision tree induction lik...
We propose an O(n4) algorithm to build the modular decomposition tree of hypergraphs of dimension 3 and show how this algorithm can be generalized to compute in O(n3k−5) time th...
Can we predict locations of future refactoring based on the development history? In an empirical study of open source projects we found that attributes of software evolution data ...
Jacek Ratzinger, Thomas Sigmund, Peter Vorburger, ...
Entropy Guided Transformation Learning (ETL) is a new machine learning strategy that combines the advantages of decision trees (DT) and Transformation Based Learning (TBL). In thi...
Answering aggregate queries like sum, count, min, max over regions containing moving objects is often needed for virtual world applications, real-time monitoring systems, etc. Sin...