This paper describes an application to the prediction of the linguistic origin of surnames. The problem can be stated as follows: `Given an input string representing a surname, decide which language the surname belongs to'. We present an approach that integrates methodologies from rule-based systems, evidential reasoning, and neural networks. Our hybrid solution maximizes the used information and allows one to deal with aspects of the problem that could have not been solved otherwise. In fact, our predictor exploits both knowledge from experts on languages (by means of a rule-based system) and knowledge automatically acquired by examples (through statistical analysis and a neural network).
Bonaventura, P., Gori, M., Scarselli, F., Salza, P., Sheng, J. (1999). A connectionist-based model for predicting the linguistic origin of surnamesIJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339). In IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339) (pp.3040-3045) [10.1109/IJCNN.1999.836042].
A connectionist-based model for predicting the linguistic origin of surnamesIJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)
Gori Marco;Scarselli Franco;
1999-01-01
Abstract
This paper describes an application to the prediction of the linguistic origin of surnames. The problem can be stated as follows: `Given an input string representing a surname, decide which language the surname belongs to'. We present an approach that integrates methodologies from rule-based systems, evidential reasoning, and neural networks. Our hybrid solution maximizes the used information and allows one to deal with aspects of the problem that could have not been solved otherwise. In fact, our predictor exploits both knowledge from experts on languages (by means of a rule-based system) and knowledge automatically acquired by examples (through statistical analysis and a neural network).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11365/36571
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