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

  • João Luís Garcia Rosa
  • Edson Françozo
Conference paper

DOI: 10.1007/3-540-44399-1_27

Volume 1952 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Garcia Rosa J.L., Françozo E. (2000) Linguistic Relations Encoding in a Symbolic- Connectionist Hybrid Natural Language Processor. In: Monard M.C., Sichman J.S. (eds) Advances in Artificial Intelligence. Lecture Notes in Computer Science, vol 1952. Springer, Berlin, Heidelberg

Abstract

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • João Luís Garcia Rosa
    • 1
  • Edson Françozo
    • 2
  1. 1.Instituto de InformáticaCampinas - SPBrazil
  2. 2.LAFAPEInstituto de Estudos da LinguagemCampinas - SPBrazil