DocumentCode
629703
Title
Semantic relationships and approximations of sets: An ontological graph based approach
Author
Pancerz, Krzysztof
Author_Institution
Univ. of Manage. & Adm., Zamość, Poland
fYear
2013
fDate
6-8 June 2013
Firstpage
62
Lastpage
69
Abstract
Approximation of sets is a fundamental notion of rough set theory (RST) proposed by Z. Pawlak. In a classic approach, considered in RST, approximation of sets is defined on the basis of an indiscernibility relation between objects in some universe of discourse. However, approximations of sets become problematic in many cases, especially, if attribute values describing objects are symbolical (e.g., words, terms, linguistic concepts, etc.). In fact, such a situation is natural in human cognition and description of the real world. Different approaches perfecting rough set theory in this area have been proposed in the literature. One of them is based on incorporating ontologies enabling us to add some new, valuable knowledge which can be used in data analysis, rule generation, reasoning, etc. In the paper, we propose to use ontological graphs in determining approximations of sets and show how ontological graphs change a look at them. The presented approach refers to a general trend in computations proposed by L. Zadeh and called “computing with words”.
Keywords
approximation theory; data mining; graph theory; ontologies (artificial intelligence); rough set theory; RST; approximations; data analysis; data mining algorithms; human cognition; indiscernibility relation; ontological graph based approach; rough set theory; rule generation; semantic relationships; Approximation methods; Data mining; Information systems; Ontologies; Pragmatics; Semantics; Set theory; approximations of sets; ontological graphs; rough sets; semantic relationships;
fLanguage
English
Publisher
ieee
Conference_Titel
Human System Interaction (HSI), 2013 The 6th International Conference on
Conference_Location
Sopot
ISSN
2158-2246
Print_ISBN
978-1-4673-5635-0
Type
conf
DOI
10.1109/HSI.2013.6577803
Filename
6577803
Link To Document