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ICANN
2009
Springer

Connectionist Models for Formal Knowledge Adaptation

10 years 10 months ago
Connectionist Models for Formal Knowledge Adaptation
Abstract. Both symbolic knowledge representation systems and artificial neural networks play a significant role in Artificial Intelligence. A recent trend in the field aims at interweaving these techniques, in order to improve robustness and performance of classification and clustering systems. In this paper, we present a novel architecture based on the connectionist adaptation of ontological knowledge. The proposed architecture was used effectively to improve image segment classification within a multimedia application scenario.
Ilianna Kollia, Nikos Simou, Giorgos B. Stamou, An
Added 26 May 2010
Updated 26 May 2010
Type Conference
Year 2009
Where ICANN
Authors Ilianna Kollia, Nikos Simou, Giorgos B. Stamou, Andreas Stafylopatis
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