Yazar
de Mel, G., Şensoy, Murat, Vasconcelos, W., Norman, T. J.
Basım Tarihi
2013-02
Basım Yeri
-
Elsevier
Konu
Logic programming, Semantic web, Knowledge-based resource selection
Tür
Süreli Yayın
Dil
İngilizce
Dijital
Evet
Yazma
Hayır
Kütüphane
Özyeğin Üniversitesi
Demirbaş Numarası
0952-1976
Kayıt Numarası
ccdfa52a-806c-4d25-8566-dac5dd5a9622
Lokasyon
Computer Science
Tarih
2013-02
Notlar
Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin
In this paper, we present Ontological Logic Programming (OLP), a novel approach that combines logic programming with ontological reasoning. OLP enables the use of ontological terms (i.e., individuals, classes and properties) directly within logic programmes. The interpretation of these terms is delegated to an ontology reasoner during the interpretation of the programme. Unlike similar approaches, OLP makes use of the full capacity of both ontological reasoning and logic programming. We evaluate the computational properties of OLP in different settings and show that its performance can be significantly improved using caching mechanisms. We then introduce a comprehensive sensor-task selection solution based on OLP and discuss the benefits one can obtain by using OLP. The solution is based on a set of interlinking ontologies that capture the crucial domain knowledge of sensor networks. We then make use of OLP to create and manage complex concepts in the domain as well as to implement effective resource-task assignment algorithms, which compute appropriate resources for tasks such that they sufficiently cover the tasks needs. We compare the advantages of OLP with a knowledge-based set-covering mechanism for resource-task selection.
DOI
10.1016/j.engappai.2012.12.003
Cilt
26
