Authors:
Ramón Alberto Carrasco
1
;
María Amparo Vila
1
and
José Galindo
2
Affiliations:
1
Universidad de Granada, Spain
;
2
Universidad de Málaga, Spain
Keyword(s):
Clustering, Flexible Queries, Data Mining, Fuzzy SQL, Fuzzy Databases.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Sensor Networks
;
Signal Processing
;
Society, e-Business and e-Government
;
Soft Computing
;
Web Information Systems and Technologies
Abstract:
At present, we have a dmFSQL server available for Oracle© Databases, programmed in PL/SQL. This server allows us to query a Fuzzy or Classical Database with the dmFSQL (data mining Fuzzy SQL) language for any data type. The dmFSQL language is an extension of the SQL language, which permits us to write flexible (or fuzzy) conditions in our queries to a fuzzy or traditional database. In this paper, we propose the use of the dmFSQL language for fuzzy queries as one of the techniques of Data Mining, which can be used to obtain the clustering results in real time. This enables us to evaluate the process of extraction of information (Data Mining) at both a practical and a theoretical level. We present a new version of the prototype, called DAPHNE, for clustering witch use dmFSQL. We consider that this model satisfies the requirements of Data Mining systems (handling of different types of data, high-level language, efficiency, certainty, interactivity, etc) and this new level of personal co
nfiguration makes the system very useful and flexible.
(More)