University of Oulu

Argumentation system for intelligent assistants using fuzzy-based reasoning T. Koivuaho (), M. Ibrahim (), F. Ummul (), and M. Oussalah () Data Science and Knowledge Engineering for Sensing Decision Support. October 2018, 608-616, https://doi.org/10.1142/9789813273238_0078

Argumentation system for intelligent assistants using fuzzy-based reasoning

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Author: Koivuaho, T.1; Ibrahim, M.1; Ummul, F.1;
Organizations: 1Centre for Ubiquitous Computing, Faculty of Information Technology and Electrical Engineering, University of Oulu. OULU, 90014- FINLAND
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.2 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2020042119541
Language: English
Published: World Scientific, 2018
Publish Date: 2020-04-21
Description:

Abstract

This paper addresses the issue of building intelligent assistant that is able to maintain sustainable conversation with the user while taking into account his emotional, personality aspects, and, at the same time, maintaining high level focus. The approach makes use four meta-features; namely, topic, emotion, personality and dialogue-act. A sequence-to sequence recurrent neural network approach was used to learn answer prototypes from Reddit.com sport corpus, while an ANFIS based approach was developed to extrapolate from the limited configurations used by the neural network to various dialogue utterances.

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Series: World Scientific proceedings series on computer engingeering and information science
ISSN: 1793-7868
ISSN-L: 1793-7868
ISBN Print: 978-981-3273-22-1
Pages: 608 - 616
DOI: 10.1142/9789813273238_0078
OADOI: https://oadoi.org/10.1142/9789813273238_0078
Host publication: Data Science and Knowledge Engineering for Sensing Decision Support. Proceedings of the 13th International FLINS Conference (FLINS 2018)
Host publication editor: Liu, Jun
Lu, Jie
Xu, Yang
Martinez, Luis
Kerre, Etienne E.
Conference: International Conference on Data Science and Knowledge Engineering for Sensing Decision Support
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Subjects:
Funding: This work is (partially) funded by the Marie Skłodowska-Curie Actions (645706-GRAGE).
Copyright information: Electronic version of an article published as Data Science and Knowledge Engineering for Sensing Decision Support. Proceedings of the 13th International FLINS Conference (FLINS 2018) https://doi.org/10.1142/9789813273238_0078 © World Scientific Publishing Co Pte Ltd.