A Knowledge Representation Example of a Fuzzy Database Implemented in PostgreSQL, with FIRST-2 and FSQL

In this article we present how to implement fuzzy databases based on the relational model. This approach includes many fuzzy attribute types, which can express the most of fuzzy knowledge types. These fuzzy attribute types include imprecise attributes, fuzzy attributes associated with one or more attributes, or with an independent meaning. In order to represent such fuzzy information we must study two aspects of fuzzy information: how to represent fuzzy data and how to represent fuzzy metaknowledge data. This second information is very important and it must be considered in any fuzzy database. This article studies the fuzzy metaknowledge data for any fuzzy attribute and how to represent both in a relational database. Finally, we apply all of this in a real example in the context of medical appointments.Sociedad Argentina de Informática e Investigación Operativ

Implementation of a fuzzy relational database. Case study: academic tutoring

This paper describes the process of implementation of a diffused relational database in the practical case of the academic tutorials of the Faculty of Engineering Sciences of the Equinoctial Technological University (UTE). For the implementation, the ANSI-SPARC database architecture was used as the methodology, which abstracts the information into levels, at the external level the functional requirements were obtained, at the conceptual level, the diffused relational model was obtained. To achieve this model, we performed the transformation of the diffuse data through mathematical models using the Fuzzy-Lookup tool and at the physical level the diffused relational database was implemented. In addition, an user interface was developed using Java through which data is entered and queries are made to the diffused relational database to verify its operation