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Abstract
In this paper we propose a novel recommendation approach using past news click data and the Neural Knowledge DNA (NK-DNA). The Neural Knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for news recommendation tasks on the MIND benchmark dataset. By taking advantages of NK-DNA, deep learning, and the SOEKS technologies, our approach can learn from users’ past behaviors to form reading preference of the user, and reuse learned knowledge for improving the recommendation performance.
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Authors (4)
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Guangjian Ning
- CUIT China
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Chunwang Wu
- CUIT China
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Haoxi Zhang
- CUIT China
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- Accepted or Published Version
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- Copyright (2021 Informa UK Limited)
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- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
-
CYBERNETICS AND SYSTEMS
no. 52,
pages 419 - 428,
ISSN: 0196-9722 - Language:
- English
- Publication year:
- 2021
- Bibliographic description:
- Ning G., Wu C., Zhang H., Szczerbicki E.: Toward Intelligent Recommendations Using the Neural Knowledge DNA// CYBERNETICS AND SYSTEMS -Vol. 52,iss. 5 (2021), s.419-428
- DOI:
- Digital Object Identifier (open in new tab) 10.1080/01969722.2020.1871229
- Verified by:
- Gdańsk University of Technology
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