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About Granular Rough Computing—Overview of Decision System Approximation Techniques and Future Perspectives
Open AccessArticle

The Auto-Diagnosis of Granulation of Information Retrieval on the Web

Department of Computer Science, Opole University of Technology, Proszkowska 76, 45-758 Opole, Poland
Algorithms 2020, 13(10), 264; https://doi.org/10.3390/a13100264
Received: 18 September 2020 / Revised: 9 October 2020 / Accepted: 13 October 2020 / Published: 16 October 2020
(This article belongs to the Special Issue Granular Computing: From Foundations to Applications)
In this paper, a postulation on the relationship between the memory structure of the brain’s neural network and the representation of information granules in the semantic web is presented. In order to show this connection, abstract operations of inducing information granules are proposed to be used for the proposed logical operations systems, hereinafter referred to as: analysis, reduction, deduction and synthesis. Firstly, the searched information is compared with the information represented by the thesaurus, which is equivalent to the auto-diagnosis of this system. Secondly, triangular norm systems (information perception systems) are built for fuzzy or vague information. These are fuzzy sets. The introduced logical operations and their logical values, denoted as problematic, hypothetical, validity and decidability, are interpreted in these fuzzy sets. In this way, the granularity of the information retrieval on the Web is determined according to the type of reasoning. View Full-Text
Keywords: granular calculation; semantic web; triangular norms; information retrieval granular calculation; semantic web; triangular norms; information retrieval
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Bryniarska, A. The Auto-Diagnosis of Granulation of Information Retrieval on the Web. Algorithms 2020, 13, 264.

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