Sub-Symbolic Knowledge Representation for Evocative Chat-Bots

G. Pilato (), A. Augello (), G. Vassallo () and S. Gaglio ()
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G. Pilato: CNR - ICAR
A. Augello: Università degli Studi di Palermo
G. Vassallo: Università degli Studi di Palermo
S. Gaglio: CNR - ICAR

A chapter in Interdisciplinary Aspects of Information Systems Studies, 2008, pp 343-349 from Springer

Abstract: 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.

Keywords: Latent Semantic Analysis; Semantic Space; Ontology Concept; Conversational Agent; Lexical Category (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2010-2_42

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DOI: 10.1007/978-3-7908-2010-2_42

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