Abstract
With widespread modernization, digitization and transformations of most of industries, Artificial Intelligence (AI) has become the key enabler in that modernization journey. AI offers substantial capabilities to solve new problems and optimise existing solutions specialising on specific problems and learning from different domains. AI solutions can be either explainable or black box ones with the latter being urged to improve since they cannot trust. Case-based Reasoning (CBR) is an explainable AI approach where solutions are provided along with relevant explanations in terms of why a solution was selected. However, CBR, like most other explainable approaches, has several limitations in terms of scalability, large data volumes, domain complexity, that reduce its ability to scale any CBR system in industrial applications. In this paper, we provide a heterogeneous CBR framework - DeepKAF where we combine CBR paradigm with Deep Learning architectures to solve complicated Natural Language Processing (NLP) problems (eg. mixed language and grammatically incorrect text).DeepKAF is built based on continuous research in the area of Deep Learning and CBR. DeepKAF has been implemented and used across different domains, test use cases and research models as an ensemble deep learning and CBR Architecture.
Original language | English |
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Title of host publication | INISTA 2020 - 2020 International Conference on INnovations in Intelligent SysTems and Applications, Proceedings |
Subtitle of host publication | INISTA 2020 |
Editors | Mirjana Ivanovic, Tulay Yildirim, Goce Trajcevski, Costin Badica, Ladjel Bellatreche, Igor Kotenko, Amelia Badica, Burcu Erkmen, Milos Savic |
Publisher | IEEE |
Pages | 1-7 |
ISBN (Electronic) | 9781728167992 |
ISBN (Print) | 9781728168005 |
DOIs | |
Publication status | Published - 11 Sept 2020 |
Event | IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) - Duration: 24 Aug 2020 → 26 Aug 2020 |
Publication series
Name | INISTA 2020 - 2020 International Conference on INnovations in Intelligent SysTems and Applications, Proceedings |
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Conference
Conference | IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) |
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Period | 24/08/20 → 26/08/20 |
Keywords
- Case-based Reasoning
- Deep Learning
- Natural Language Processing
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Nikolaos Polatidis
- School of Arch, Tech and Eng - Principal Lecturer
- Centre for Secure, Intelligent and Usable Systems
Person: Academic