Symbolic Systems in Artificial Intelligence which are based on formal logic and deductive reasoning are fundamentally different from Artificial Intelligence systems based on artificial neural networks, such as deep learning approaches. The difference is not only in their inner workings and general approach, but also with respect to capabilities. Neural-symbolic Integration, as a field of study, aims to bridge between the two paradigms. In this paper, we will discuss neural-symbolic integration in its relation to the Semantic Web field, with a focus on promises and possible benefits for both, and report on some current research on the topic.

Hitzler, P., Bianchi, F., Ebrahimi, M., Sarker, M. (2020). Neural-symbolic integration and the Semantic Web. SEMANTIC WEB, 11(1), 3-11 [10.3233/SW-190368].

Neural-symbolic integration and the Semantic Web

Bianchi, Federico;
2020

Abstract

Symbolic Systems in Artificial Intelligence which are based on formal logic and deductive reasoning are fundamentally different from Artificial Intelligence systems based on artificial neural networks, such as deep learning approaches. The difference is not only in their inner workings and general approach, but also with respect to capabilities. Neural-symbolic Integration, as a field of study, aims to bridge between the two paradigms. In this paper, we will discuss neural-symbolic integration in its relation to the Semantic Web field, with a focus on promises and possible benefits for both, and report on some current research on the topic.
Articolo in rivista - Articolo scientifico
artificial neural networks; deductive reasoning; deep learning; Neural-symbolic integration;
neural-symbolic, semantic web, reasoning, neural networks
English
2020
11
1
3
11
reserved
Hitzler, P., Bianchi, F., Ebrahimi, M., Sarker, M. (2020). Neural-symbolic integration and the Semantic Web. SEMANTIC WEB, 11(1), 3-11 [10.3233/SW-190368].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/246561
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