Deep learning powered question-answering framework for organizations digital transformation
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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