Deep learning powered question-answering framework for organizations digital transformation

dc.contributor.author Carvalho,NR en
dc.contributor.author Luís Soares Barbosa en
dc.contributor.other 5603 en
dc.date.accessioned 2020-06-16T09:09:56Z
dc.date.available 2020-06-16T09:09:56Z
dc.date.issued 2019 en
dc.description.abstract In the context of digital transformation by governments, the public sector and other organizations, many information is moving to digital platforms. Chatbots and similar question-answering systems are becoming popular to answer information queries, opposed to browsing online repositories or webpages. State-of-the-art approaches for these systems may be laborious to implement, hard to train and maintain, and also require a high level of expertise. is work explores the definition of a generic framework to systematically build question-answering systems. A sandbox implementation of this framework enables the deployment of turnkey systems, directly from already existing collections of documents. ese systems can then be used to provide a question-answering system communication channel to enrich the organization digital presence. © 2019 Association for Computing Machinery. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/11223
dc.identifier.uri http://dx.doi.org/10.1145/3326365.3326375 en
dc.language eng en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Deep learning powered question-answering framework for organizations digital transformation en
dc.type Publication en
dc.type conferenceObject en
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