We present a methodology for the modeling of complex program behavior in CLP. In the first part we present an informal description about how to represent a system in CLP. At its ...
Automatically categorizing documents into pre-defined topic hierarchies or taxonomies is a crucial step in knowledge and content management. Standard machine learning techniques ...
We present a technique to approximate the worst-case execution time that combines structural analysis with a loop-bounding algorithm based on local induction variable analysis. St...
The Web is now a huge information repository with a rich semantic structure that, however, is primarily addressed to human understanding rather than automated processing by a compu...
Inductive inference can be considered as one of the fundamental paradigms of algorithmic learning theory. We survey results recently obtained and show their impact to potential ap...