Paper Info
Title
Attribute-Oriented Fuzzy Generalization In Proximity- And Similarity-Based Relational Database Systems
Abstract
In this article we investigate an attribute-oriented induction approach for acquisition of abstract knowledge from data stored in a fuzzy database environment. We utilize a proximity-based fuzzy database schema as the medium carrying the original information, where lack of precise information about an entity can be reflected via multiple attribute values, and the classical equivalence relation is replaced with the broader fuzzy proximity relation. We analyze in detail the process of attribute-oriented induction by concept hierarchies, utilizing the original properties of fuzzy databases to support this established data mining technique. In our approach we take full advantage of the implicit knowledge about the similarity of original attribute values, included by default in the investigated fuzzy database schemas. (c) 2007 Wiley Periodicals, Inc.
Year
DOI
Venue
2007
10.1002/int.20227
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
Keywords
Field
DocType
relational database system,data mining
Data mining,Database model,Computer science,View,Database schema,Artificial intelligence,Information retrieval,Fuzzy logic,Relation (database),Database design,Intelligent database,Relational database management system,Machine learning
Journal
Volume
Issue
ISSN
22
7
0884-8173
Citations 
PageRank 
References 
2
0.37
18
Authors
2
Name
Order
Citations
PageRank
Rafal A. Angryk127145.56
Frederick E. Petry256269.24