Deep Learning Powered Question-Answering Framework for Organizations Digital Transformation

Carvalho, Nuno and Soares Barbosa, Luís, "Deep Learning Powered Question-Answering Framework for Organizations Digital Transformation" 12th International Conference on Theory and Practice of Electronic Governance (ICEGOV2019), Melbourne, 2019/04/03-05.

Document type:
Conference Publication
Collection:
UNU-EGOV Conference Publications

Metadata
Documents
Links
Versions
Statistics
  • Attached Files (Some files may be inaccessible until you login with your UNU Collections credentials)
    Name Description MIMEType Size Downloads
    p076-Ramos-Carvalho.pdf Full paper (open access) application/pdf 669.29KB
  • Sub-type Conference paper
    Author Carvalho, Nuno
    Soares Barbosa, Luís
    Title Deep Learning Powered Question-Answering Framework for Organizations Digital Transformation
    Event Series International Conference on Theory and Practice of Electronic Governance (ICEGOV)
    Publication Date 2019-05
    Place of Publication New York
    Publisher ACM Press
    Pages 76-79
    Title of Event 12th International Conference on Theory and Practice of Electronic Governance (ICEGOV2019)
    Date of Event 2019/04/03-05
    Place of Event Melbourne
    Language eng
    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. This 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. These systems can then be used to provide a question-answering system communication channel to enrich the organization digital presence.
    Keyword deep learning
    question-answering system
    digital transformation
    Copyright Holder ACM Press
    Copyright Year 2019
    Copyright type All rights reserved
    ISBN 9781450366441
    DOI 10.1145/3326365.3326375
  • Versions
    Version Filter Type
  • Citation counts
    Google Scholar Search Google Scholar
    Access Statistics: 735 Abstract Views, 651 File Downloads  -  Detailed Statistics
    Created: Tue, 21 May 2019, 19:14:44 JST by Mario Peixoto on behalf of UNU EGOV