Using dmFSQL for financial clustering

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 configuration makes the system very useful and flexible.