A Relational Model for the Possibilistic Valid-time Approach

In real world, it is very common that some objects or concepts have properties with a time-variant or timerelated nature. Modelling this kind of objects or concepts in a (relational) database schema is possible, but time-variant and time-related attributes have an impact on the consistency of the entire database and must be appropriately managed. Therefore, temporal database models have been proposed to deal with this problem in the literature. Time can be affected by imprecision, vagueness and / or uncertainty, since existing time measuring devices are inherently imperfect. Additionally, human beings manage time using temporal indications and temporal notions, which may also be imprecise. However, the imperfection in human-used temporal indications is supported by human interpretation, whereas information systems need appropriate support in order to accomplish this task. Several proposals for dealing with such imperfections when modelling temporal data exist. Some of these proposals transform the temporal data into a compact representation but there is not a formal model for managing and handling uncertainty regarding temporal information. In this work we present a novel model to deal with imprecision in valid-time databases together with the definition and implementation of the data manipulation language, DML.Junta de Andalucia P07-TIC-03175 BES-2009-013805 TIN2008-0206

Bipolar fuzzy querying of temporal databases

Temporal databases handle temporal aspects of the objects they describe with an eye to maintaining consistency regarding these temporal aspects. Several techniques have allowed these temporal aspects, along with the regular aspects of the objects, to be defined and queried in an imprecise way. In this paper, a new technique is proposed, which allows using both positive and negative -possibly imprecise- information in querying relational temporal databases. The technique is discussed and the issues which arise are dealt with in a consistent way

A comparison of approaches to model uncertainty in time intervals

Information systems model parts of reality by representing properties of real-world objects or concepts. As real objects or concepts often have temporal aspects, temporal notions such as time intervals are often represented. However, these may contain imperfections like uncertainties, complicating their representations. A very important purpose of information systems is to be able to query them to retrieve information, but representations of temporal notions containing uncertainties severely complicate querying. Thus, several soft computing techniques have been proposed to represent time intervals subject to uncertainties in a semantically sound way and to reason with them in a semantically sound and useful way. In the presented work, two frameworks designed for this are compared. It is found that, despite slight differences in the way these frameworks represent intervals, they provide the same results when reasoning about time intervals subject to uncertainty

An elemental processor of fuzzy SQL

This paper reports an alternative for implementing an SQL fuzzy extension on a Fuzzy Relational Database System. This proposal tries to build an FSQL processor using representation and manipulation mechanisms offered by the RDBMS which operates as a host. For this purpose, we are based our work on the formulation of a theoretical model of Fuzzy Relational Databases, on the adoption of a scheme for the representation and implementation of fuzzy information on conventional RDBMS, and on the tools for the development of applications available in the host RDBMS. Finally, the FSQL processor is able to translate sentences formulated in FSQL into classical SQL sentences executed directly by the RDBMS adopted as host

A fuzzy database engine for mongoDB

This study has been partially supported by the MCIN/AEI/10.13039/501100011033 and FEDER: “Una manera de hacer Europa” under project PGC2018‐096156‐B‐I00: Recuperación y Descripción de Imágenes mediante Lenguaje Natural usando Técnicas de Aprendizaje Profundo y Computación Flexible.Big Data are a paradigm through which valuable information is achieved through the analysis of a large amount of data. The sources of these data can be varied, from data streams that will be processed in real time, to the exploitation of transactional data stored in databases. For this last use, due to their scalability, the NoSQL databases, like mongoDB, a DBMS oriented to documents, have been consolidated as a powerful tool for the storage and processing of large volumes of data. On the other hand, information sources for Big Data algorithms can contain imprecise information, and the way to obtain, aggregate and present results can have an imprecise nature as well. For this reason, it is useful to provide fuzzy extensions to these DBMSs. In the case of MongoDB, there are few proposals and not very complete. This paper describes fzMongoDB, a fuzzy database engine that provides the mongoDB database with the capacity to store documents with imprecise information and to retrieve them in a flexible way. It is implemented and integrated on the mongoDB server using the resources it provides. The model and implementation of fzMongoDB also includes an indexing mechanism that accelerates the retrieval process on fuzzy queries. Also, the performance of these indexing mechanisms is evaluated.Universidad de GranadaMCIN/AEI/10.13039/501100011033FEDER: “Una manera de hacer Europa” PGC2018‐096156‐B‐I0

An elemental processor of fuzzy SQL

This paper reports an alternative for implementing an SQL fuzzy extension on a Fuzzy Relational Database System. This proposal tries to build an FSQL processor using representation and manipulation mechanisms offered by the RDBMS which operates as a host. For this purpose, we are based our work on the formulation of a theoretical model of Fuzzy Relational Databases, on the adoption of a scheme for the representation and implementation of fuzzy information on conventional RDBMS, and on the tools for the development of applications available in the host RDBMS. Finally, the FSQL processor is able to translate sentences formulated in FSQL into classical SQL sentences executed directly by the RDBMS adopted as host

Client/server architecture for fuzzy relational databases

This paper shows a FRDBMS architecture whose main characteristics are: 1) it is implemented entirely on classical RDBMS just using the resources provided by them, 2) it preserves all the operations and qualities of the host RDBMS and gives them more power adding new capabilities to deal with "fuzzy" information and 3) it provides a frame to develop applications which exploit fuzzy information

Client/server architecture for fuzzy relational databases

This paper shows a FRDBMS architecture whose main characteristics are: 1) it is implemented entirely on classical RDBMS just using the resources provided by them, 2) it preserves all the operations and qualities of the host RDBMS and gives them more power adding new capabilities to deal with "fuzzy" information and 3) it provides a frame to develop applications which exploit fuzzy information

Client/server architecture for fuzzy relational databases

This paper shows a FRDBMS architecture whose main characteristics are: 1) it is implemented entirely on classical RDBMS just using the resources provided by them, 2) it preserves all the operations and qualities of the host RDBMS and gives them more power adding new capabilities to deal with fuzzy information and 3) it provides a frame to develop applications which exploit fuzzy information