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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing

Abstract

ABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest neighbors), logistic regression, and AdaBoost in classification tasks, and the results show that our approach is very promising with regard to the enhancement of the accuracy of knowledge-based predictions required in complex decisionmaking problems.

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Authors (3)

Keywords

Details

Category:
Articles
Type:
artykuł w czasopiśmie wyróżnionym w JCR
Published in:
CYBERNETICS AND SYSTEMS no. 47, edition 1-2, pages 140 - 148,
ISSN: 0196-9722
Language:
English
Publication year:
2016
Bibliographic description:
Zhang H., Sanin C., Szczerbicki E.: When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing// CYBERNETICS AND SYSTEMS. -Vol. 47, iss. 1-2 (2016), s.140-148
DOI:
Digital Object Identifier (open in new tab) 10.1080/01969722.2016.1128776
Verified by:
Gdańsk University of Technology

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