Advances in Artificial Intelligence

Volume 1952 of the series Lecture Notes in Computer Science pp 259-268

Linguistic Relations Encoding in a Symbolic- Connectionist Hybrid Natural Language Processor

  • João Luís Garcia RosaAffiliated withInstituto de Informática
  • , Edson FrançozoAffiliated withLAFAPE, Instituto de Estudos da Linguagem

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In recent years, the Natural Language Processing scene has witnessed the steady growth of interest in connectionist modeling. The main appeal of such an approach is that one does not have to determine the grammar rules in advance: the learning abilities displayed by such systems take care of input regularities. Better and faster learning can be obtained through the implementation of a symbolic-connectionist hybrid system. Such system combines the advantages of symbolic approaches, by introducing symbolic rules as network connection weights, with the advantages of connectionism. In a hybrid system called HTRP, words within a sentence are represented by means of semantic features. The features for the verbs are arranged along certain semantic dimensions, and are mutually exclusive within each dimension. One may infer that this happens because of the semantic features encoded in the network inputs.