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2021 | OriginalPaper | Buchkapitel

Linguistic Summaries Using Interval-Valued Fuzzy Representation of Imprecise Information - An Innovative Tool for Detecting Outliers

verfasst von : Agnieszka Duraj, Piotr S. Szczepaniak

Erschienen in: Computational Science – ICCS 2021

Verlag: Springer International Publishing

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Abstract

The practice of textual and numerical information processing often involves the need to analyze and test a database for the presence of items that differ substantially from other records. Such items, referred to as outliers, can be successfully detected using linguistic summaries. In this paper, we extend this approach by the use of non-monotonic quantifiers and interval-valued fuzzy sets. The results obtained by this innovative method confirm its usefulness for outlier detection, which is of significant practical relevance for database analysis applications.

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Titel: Linguistic Summaries Using Interval-Valued Fuzzy Representation of Imprecise Information - An Innovative Tool for Detecting Outliers
verfasst von: Agnieszka Duraj
Piotr S. Szczepaniak
Verlag: Springer International Publishing
Buch: Computational Science – ICCS 2021
Print ISBN: 978-3-030-77979-5

Electronic ISBN: 978-3-030-77980-1

Copyright-Jahr: 2021
DOI: https://doi.org/10.1007/978-3-030-77980-1_38

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