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.
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Pilato, G., Augello, A., Vassallo, G., Gaglio, S. (2008). Sub-Symbolic Knowledge Representation for Evocative Chat-Bots. In: Interdisciplinary Aspects of Information Systems Studies. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2010-2_42
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DOI: https://doi.org/10.1007/978-3-7908-2010-2_42
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-2009-6
Online ISBN: 978-3-7908-2010-2
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