6533b829fe1ef96bd128a3ee

RESEARCH PRODUCT

Sub-Symbolic Knowledge Representation for Evocative Chat-Bots

Agnese AugelloGiovanni PilatoGiorgio VassalloSalvatore GaglioSalvatore Gaglio

subject

Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniKnowledge representation and reasoningLatent semantic analysisOntology Conceptbusiness.industryComputer scienceWordNetOntology (information science)Part of speechcomputer.software_genreArtificial intelligenceDialog systemLayer (object-oriented design)businesssemantic space chatbotcomputerNatural language processing

description

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.

yearjournalcountryeditionlanguage
2008-01-01
10.1007/978-3-7908-2010-2_42https://dx.doi.org/10.1007/978-3-7908-2010-2_42