Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61787
Title: Human Feedback and Knowledge Discovery: Towards Cognitive Systems Optimization
Contributor(s): de Oliveira, Caterine Silva (author); Sanin, Cesar  (author)orcid ; Szczerbicki, Edward (author)
Publication Date: 2020
Open Access: Yes
DOI: 10.1016/j.procs.2020.09.179
Handle Link: https://hdl.handle.net/1959.11/61787
Abstract: 

Current computer vision systems, especially those using machine learning techniques are data-hungry and frequently only perform well when dealing with patterns they have seen before. As an alternative, cognitive systems have become a focus of attention for applications that involve complex visual scenes, and in which conditions may vary. In theory, cognitive applications uses current machine learning algorithms, such as deep learning, combined with cognitive abilities that can broadly generalize to many tasks. However, in practice, perceiving the environment and adapting to unforeseen changes remains elusive, especially for real time applications that has to deal with high-dimensional data processing with strictly low latency. The challenge is not only to extract meaningful information from this data, but to gain knowledge and also to discover insight to optimize the performance of the system. We envision to tackle these difficulties by bringing together the best of machine learning and human cognitive capabilities in a collaborative way. For that, we propose an approach based on a combination of Human-in-the-Loop and Knowledge Discovery in which feedback is used to discover knowledge by enabling users to interactively explore and identify useful information so the system can be continuously trained to gain previously unknown knowledge and also generate new insights to improve human decisions.

Publication Type: Conference Publication
Conference Details: KES 2020: 24th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES) Conference, Virtual Conference, 16th to 18th of September, 2020
Source of Publication: Procedia Computer Science, v.176, p. 3093-3102
Publisher: Elsevier BV
Place of Publication: The Netherlands
ISSN: 1877-0509
Fields of Research (FoR) 2020: 4602 Artificial intelligence
Peer Reviewed: Yes
HERDC Category Description: E1 Refereed Scholarly Conference Publication
Appears in Collections:Conference Publication
School of Science and Technology

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