@inproceedings{8272a835f93848328860a5b33eaa3f74,
title = "Rough set approximations in formal concept analysis",
abstract = "Conventional set approximations are based on a set of attributes; however, these approximations cannot relate an object to the corresponding attribute. In this study, a new model for set approximation based on individual attributes is proposed for interval-valued data. Defining an indiscernibility relation is omitted since each attribute value itself has a set of values. Two types of approximations, single- and multiattribute approximations, are presented. A multi-attribute approximation has two solutions: a maximum and a minimum solution. A maximum solution is a set of objects that satisfy the condition of approximation for at least one attribute. A minimum solution is a set of objects that satisfy the condition for all attributes. The proposed set approximation is helpful in finding the features of objects relating to condition attributes when interval-valued data are given. The proposed model contributes to feature extraction in interval-valued information systems.",
keywords = "grey numbers, grey system theory, indeterministic information systems, interval data, rough sets, set approximations",
author = "Daisuke Yamaguchi and Atsuo Murata and Li, {Guo Dong} and Masatake Nagai",
year = "2010",
doi = "10.1007/978-3-642-14467-7_12",
language = "English",
isbn = "3642144667",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "226--235",
booktitle = "Transactions on Rough Sets XII",
note = "Rough Set and Knowledge Technology Conference, RSKT 2008 ; Conference date: 01-05-2008 Through 01-05-2008",
}