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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 1/2017

17-09-2016 | Original Article

Three-way conceptual approach for cognitive memory functionalities

Authors: Radhika Shivhare, Aswani Kumar Cherukuri

Published in: International Journal of Machine Learning and Cybernetics | Issue 1/2017

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Abstract

Human brain represents the information and stores it as memory. They are stored in different parts of the brain and are linked together by associations. When a cue is provided, the memory is recalled through association. Encoding of the real world information is in the form of object-attribute relation. It is possible to perform both positive recall (object having the attribute and attribute shared by object) and negative recalls (object not having the attribute and attribute not shared by object) from memory. It is evident from literature that the formal concept analysis (FCA) based on bidirectional associative memory (BAM) performs only positive recall from memory. In this paper, FCA based on BAM is extended to three-way formal concept analysis (3WFCA) to achieve a more precise recall. In this extended model, both positive recall and negative recall are performed. In order to achieve this objective, an extra operator namely negative operator is added. The proposed model is validated with an experiment on real world scenario. We also presented the connection of the proposal with long term potentiation (LTP) and Hippocampus of the human brain.
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Metadata
Title
Three-way conceptual approach for cognitive memory functionalities
Authors
Radhika Shivhare
Aswani Kumar Cherukuri
Publication date
17-09-2016
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 1/2017
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-016-0593-0

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