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Sub-Symbolic Knowledge Representation for Evocative Chat-Bots

In: Interdisciplinary Aspects of Information Systems Studies

Author

Listed:
  • G. Pilato

    (CNR - ICAR)

  • A. Augello

    (Università degli Studi di Palermo)

  • G. Vassallo

    (Università degli Studi di Palermo)

  • S. Gaglio

    (CNR - ICAR
    Università degli Studi di Palermo)

Abstract

A sub-symbolic knowledge representation oriented to the enhancement of chat bot interaction is proposed. The result of the technique is the introduction of a semantic sub-symbolic layer to a traditional ontology-based knowledge representation. This layer is obtained mapping the ontology concepts into a semantic space built through Latent Semantic Analysis (LSA) technique and it is embedded into a conversational agent. This choice leads to a chat-bot with “evocative” capabilities whose knowledge representation framework is composed of two areas: the rational and the evocative one. As a standard ontology we have chosen the well-founded WordNet lexical dictionary, while as chat-bot the ALICE architecture. Experimental trials involving four lexical categories of WordNet have been conducted, and an example of interaction is shown at the end of the paper.

Suggested Citation

  • G. Pilato & A. Augello & G. Vassallo & S. Gaglio, 2008. "Sub-Symbolic Knowledge Representation for Evocative Chat-Bots," Springer Books, in: Interdisciplinary Aspects of Information Systems Studies, pages 343-349, Springer.
    • Handle: RePEc:spr:sprchp:978-3-7908-2010-2_42
    DOI: 10.1007/978-3-7908-2010-2_42
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