Many applications make use of named entity classification. Machine learning is the preferred technique adopted for many named entity classification methods where the choice of feat...
The management of knowledge, i.e. knowing what is known and the ability to exploit it is a burning issue for most organizations. Though knowledge management has a strong social pe...
Markus Zanker, Sergiu Gordea, Marius-Calin Silaghi
This paper develops a theory of frequency domain invariants in computer vision. We derive novel identities using spherical harmonics, which are the angular frequency domain analog ...
The aim of this work is the design of a framework for the revision of knowledge in abductive reasoning agents, based on interaction. We address issues such as: how to exploit knowl...
The goal of this paper is to develop methods to handle inconsistent knowledge elicited from multiple sources. Knowledge is represented using predicates that define relationships w...