Introduction

Pawel Delimata; Mikhail Ju Moshkov; Andrzej Skowron; Zbigniew Suraj

doi:10.1007/978-3-540-85638-2_1

Introduction

Pawel Delimata^*, Mikhail Ju Moshkov, Andrzej Skowron, Zbigniew Suraj

^*Corresponding author for this work

Applied Mathematics and Computational Science

Research output: Chapter in Book/Report/Conference proceeding › Foreword/postscript › peer-review

Abstract

The monograph is devoted to the study of inhibitory rules. In contrast to deterministic (standard) rules which have the relation attribute = value on the right-hand side, inhibitory rules have on the right-hand side the relation attibute ≠ value. For information systems [60, 63, 72], we consider inhibitory association rules which on the right-hand side can have an arbitrary attribute. For decision systems (decision tables) [60], we consider inhibitory decision rules containing on the right-hand side the decision attribute. It is worthwhile mentioning that in the rough set approach the decision rules are used for extension of approximations of concepts from given samples of objects on the whole universe of objects (see, e.g., [5, 6, 75]).

Original language	English (US)
Title of host publication	Inhibitory Rules in Data Analysis
Subtitle of host publication	A Rough Set Approach
Editors	Pawel Delimata, Zbigniew Suraj, Mikhail Moshkov, Andrzej Skowron
Pages	1-8
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-540-85638-2_1
State	Published - 2009

Publication series

Name	Studies in Computational Intelligence
Volume	163
ISSN (Print)	1860-949X

ASJC Scopus subject areas

Artificial Intelligence

Access to Document

10.1007/978-3-540-85638-2_1

Cite this

@inbook{a4e0329e061444aa9f5ff6be8ec71122,

title = "Introduction",

abstract = "The monograph is devoted to the study of inhibitory rules. In contrast to deterministic (standard) rules which have the relation attribute = value on the right-hand side, inhibitory rules have on the right-hand side the relation attibute ≠ value. For information systems [60, 63, 72], we consider inhibitory association rules which on the right-hand side can have an arbitrary attribute. For decision systems (decision tables) [60], we consider inhibitory decision rules containing on the right-hand side the decision attribute. It is worthwhile mentioning that in the rough set approach the decision rules are used for extension of approximations of concepts from given samples of objects on the whole universe of objects (see, e.g., [5, 6, 75]).",

author = "Pawel Delimata and Moshkov, {Mikhail Ju} and Andrzej Skowron and Zbigniew Suraj",

year = "2009",

doi = "10.1007/978-3-540-85638-2_1",

language = "English (US)",

isbn = "9783540856375",

series = "Studies in Computational Intelligence",

pages = "1--8",

editor = "Pawel Delimata and Zbigniew Suraj and Mikhail Moshkov and Andrzej Skowron",

booktitle = "Inhibitory Rules in Data Analysis",

}

Introduction. / Delimata, Pawel; Moshkov, Mikhail Ju; Skowron, Andrzej et al.
Inhibitory Rules in Data Analysis: A Rough Set Approach. ed. / Pawel Delimata; Zbigniew Suraj; Mikhail Moshkov; Andrzej Skowron. 2009. p. 1-8 (Studies in Computational Intelligence; Vol. 163).

Research output: Chapter in Book/Report/Conference proceeding › Foreword/postscript › peer-review

TY - CHAP

T1 - Introduction

AU - Delimata, Pawel

AU - Moshkov, Mikhail Ju

AU - Skowron, Andrzej

AU - Suraj, Zbigniew

PY - 2009

Y1 - 2009

N2 - The monograph is devoted to the study of inhibitory rules. In contrast to deterministic (standard) rules which have the relation attribute = value on the right-hand side, inhibitory rules have on the right-hand side the relation attibute ≠ value. For information systems [60, 63, 72], we consider inhibitory association rules which on the right-hand side can have an arbitrary attribute. For decision systems (decision tables) [60], we consider inhibitory decision rules containing on the right-hand side the decision attribute. It is worthwhile mentioning that in the rough set approach the decision rules are used for extension of approximations of concepts from given samples of objects on the whole universe of objects (see, e.g., [5, 6, 75]).

AB - The monograph is devoted to the study of inhibitory rules. In contrast to deterministic (standard) rules which have the relation attribute = value on the right-hand side, inhibitory rules have on the right-hand side the relation attibute ≠ value. For information systems [60, 63, 72], we consider inhibitory association rules which on the right-hand side can have an arbitrary attribute. For decision systems (decision tables) [60], we consider inhibitory decision rules containing on the right-hand side the decision attribute. It is worthwhile mentioning that in the rough set approach the decision rules are used for extension of approximations of concepts from given samples of objects on the whole universe of objects (see, e.g., [5, 6, 75]).

UR - http://www.scopus.com/inward/record.url?scp=51849105540&partnerID=8YFLogxK

U2 - 10.1007/978-3-540-85638-2_1

DO - 10.1007/978-3-540-85638-2_1

M3 - Foreword/postscript

AN - SCOPUS:51849105540

SN - 9783540856375

T3 - Studies in Computational Intelligence

SP - 1

EP - 8

BT - Inhibitory Rules in Data Analysis

A2 - Delimata, Pawel

A2 - Suraj, Zbigniew

A2 - Moshkov, Mikhail

A2 - Skowron, Andrzej

ER -

Introduction

Abstract

Publication series

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this