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dc.contributor.authorGriol, David
dc.contributor.authorCallejas Carrión, Zoraida 
dc.date.accessioned2019-12-17T11:52:57Z
dc.date.available2019-12-17T11:52:57Z
dc.date.issued2016
dc.identifier.citationDavid Griol and Zoraida Callejas, “A Neural Network Approach to Intention Modeling for User-Adapted Conversational Agents,” Computational Intelligence and Neuroscience, vol. 2016, Article ID 8402127, 11 pages, 2016. [https://doi.org/10.1155/2016/8402127]es_ES
dc.identifier.urihttp://hdl.handle.net/10481/58376
dc.description.abstractSpoken dialogue systems have been proposed to enable a more natural and intuitive interaction with the environment andhuman-computer interfaces. In this contribution, we present a framework based on neural networks that allows modeling of theuser’s intention during the dialogue and uses this prediction todynamically adapt the dialoguemodel of the system taking intoconsideration the user’s needs and preferences. We have evaluated our proposal to develop a user-adapted spoken dialogue systemthat facilitates tourist information and services and provide a detailed discussion of the positive influence of our proposal in thesuccess of the interaction, the information and services provided, and the quality perceived by the users.es_ES
dc.language.isoenges_ES
dc.publisherHindawies_ES
dc.rightsAtribución 3.0 España*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.titleA Neural Network Approach to Intention Modeling forUser-Adapted Conversational Agentses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.identifier.doi10.1155/2016/8402127


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Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España