Flexible data queries

Miroslav Hudec

doi:10.18267/j.aip.21

Abstract

The Structured Query Language (SQL) has been established as a standard for querying relational databases. However, users face the problem how to define their requirements for data by the exact query conditions. This work examines advantages of fuzzy queries, which provide a better representation of the user requirements by expressing imprecise conditions through linguistic terms. Further, the paper discusses solving empty and overabundant answer problems, revealing similarities in database entities and applying preferences in query conditions. Finally, paper discusses practical realisations of fuzzy queries.

Highlights

A query against a collection of data provides a formal description of the items of interest to the user posing this query [12]
The suggested procedure works in the following way: the user chooses one municipality and relevant indicators
The usefulness of the Structured Query Language (SQL) for data selection from relational databases has been proven in many information systems

Summary

Introduction

A query against a collection of data (in database) provides a formal description of the items of interest to the user posing this query [12]. For querying relational databases the Structured Query Language (SQL) has been developed. SQL queries use two-valued Boolean concepts (logical conditions) to describe the entities users are looking for e.g. select municipalities where altitude above sea level is greater than 1000 m. From the computational point of view this is powerful way for selecting a sub set of entities from a database. On the other side of a database are people which use the natural language in communication, searching for useful information and reasoning. For people it is more convenient to use the concept based on natural language in data selection processes

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Conclusion