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Conversational artificial intelligence - demystifying statistical vs linguistic NLP solutions

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dc.contributor.author Panesar, Kulvinder es_ES
dc.date.accessioned 2020-06-01T15:54:40Z
dc.date.available 2020-06-01T15:54:40Z
dc.date.issued 2020-05-26
dc.identifier.uri http://hdl.handle.net/10251/144774
dc.description.abstract [EN] This paper aims to demystify the hype and attention on chatbots and its association with conversational artificial intelligence. Both are slowly emerging as a real presence in our lives from the impressive technological developments in machine learning, deep learning and natural language understanding solutions. However, what is under the hood, and how far and to what extent can chatbots/conversational artificial intelligence solutions work – is our question. Natural language is the most easily understood knowledge representation for people, but certainly not the best for computers because of its inherent ambiguous, complex and dynamic nature. We will critique the knowledge representation of heavy statistical chatbot solutions against linguistics alternatives. In order to react intelligently to the user, natural language solutions must critically consider other factors such as context, memory, intelligent understanding, previous experience, and personalized knowledge of the user. We will delve into the spectrum of conversational interfaces and focus on a strong artificial intelligence concept. This is explored via a text based conversational software agents with a deep strategic role to hold a conversation and enable the mechanisms need to plan, and to decide what to do next, and manage the dialogue to achieve a goal. To demonstrate this, a deep linguistically aware and knowledge aware text based conversational agent (LING-CSA) presents a proof-of-concept of a non-statistical conversational AI solution. es_ES
dc.language Inglés es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Journal of Computer-Assisted Linguistic Research es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Conversational artificial intelligence es_ES
dc.subject Knowledge representation es_ES
dc.subject Machine/deep learning es_ES
dc.subject Natural language understanding/processing es_ES
dc.subject Role and reference grammar es_ES
dc.title Conversational artificial intelligence - demystifying statistical vs linguistic NLP solutions es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/jclr.2020.12932
dc.rights.accessRights Abierto es_ES
dc.description.bibliographicCitation Panesar, K. (2020). Conversational artificial intelligence - demystifying statistical vs linguistic NLP solutions. Journal of Computer-Assisted Linguistic Research. 4(1):47-79. https://doi.org/10.4995/jclr.2020.12932 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/jclr.2020.12932 es_ES
dc.description.upvformatpinicio 47 es_ES
dc.description.upvformatpfin 79 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 4 es_ES
dc.description.issue 1 es_ES
dc.identifier.eissn 2530-9455
dc.relation.pasarela OJS\12932 es_ES
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