Neural Networks Representation For Semantic Networks
Nabil M. Hewahi, Yaser S. Al Khateeb · 2020
Semantic network is one of the very well-known knowledge representation approaches. In various cases there is knowledge inaccuracy or incompleteness, such problems can be overcome through machine learning. In this paper we present an approach to convert semantic networks to neural networks to be ready for machine learning process. The conversion process considers all possible concepts and relations in the semantic network whether they already exist or not. The proposed neural network structure has various and several layers, such as concepts layer, relation layer and concepts and relation layer. For the learning process, it is proposed to have independent training for several neural networks.