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Advances in Rough and Soft Clustering: Meta-Clustering, Dynamic Clustering, Data-Stream Clustering Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Definability in Incomplete Information Tables

Authors : Mengjun Hu, Yiyu Yao

Published in: Rough Sets

Publisher: Springer International Publishing

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Abstract

This paper investigates the issues related to definability in an incomplete information table by using interval sets. We review the existing results pertaining to definability in a complete information table. We generalize the satisfiability of formulas in a description language in a complete table to a pair of strong and weak satisfiability of formulas in an incomplete table, which leads to an interval-set based interpretation of formulas. While we have definable sets in a complete table, we have definable interval sets in an incomplete table. The results are useful for studying concept analysis and approximations with incomplete tables.

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previous chapter Probabilistic Estimation for Generalized Rough Modus Ponens and Rough Modus Tollens
next chapter Rough Sets by Indiscernibility Relations in Data Sets Containing Possibilistic Information
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Metadata
Title
Definability in Incomplete Information Tables
Authors
Mengjun Hu
Yiyu Yao
Copyright Year
2016
Book
Rough Sets

Print ISBN: 978-3-319-47159-4

Electronic ISBN: 978-3-319-47160-0

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-47160-0_16

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