Paper Info
Title
Semi-structured decision rules in object-oriented rough set models for Kansei engineering
Abstract
Decision rule generation from Kansei data using rough set theory is one of the most hot topics in Kansei engineering. Usually, Kansei data have various types of scheme, however, Pawlak's "traditional" rough set theory treats structured data mainly, that is, decision tables with fixed attributes and no hierarchy among data. On the other hand, Kudo and Murai have proposed the object-oriented rough set model which treats structural hierarchies among objects. In this paper, we propose semi-structured decision rules in the object-oriented rough set model to represent structural characteristics among objects, which enable us to consider characteristics of hierarchical data by rough sets.
Year
DOI
Venue
2007
10.1007/978-3-540-72458-2_27
RSKT
Keywords
Field
DocType
kansei data,semi-structured decision rule,decision table,structural characteristic,decision rule generation,rough set theory,object-oriented rough set model,rough set,kansei engineering,hierarchical data,decision rule,object oriented,structured data
Decision rule,Data mining,Decision table,Computer science,Kansei engineering,Kansei,Rough set,Artificial intelligence,Data model,Hierarchical database model,Machine learning,Dominance-based rough set approach
Conference
Volume
ISSN
Citations 
4481
0302-9743
3
PageRank 
References 
Authors
0.72
3
2
Name
Order
Citations
PageRank
Yasuo Kudo19526.41
Tetsuya Murai218642.10