Fuzzy clustering algorithms for imprecise database queries: Automatic generation of fuzzy sets based on the natural distribution of data

Nowadays database management systems are one of the most critical resources in every company. Despite advanced possibilities of SQL, relational database management systems do not support flexible query conditions. The problem of extending database systems with natural language expressions is a matter of many research centers. The basic idea of presented research is to extend an existing query language and make database systems able to satisfy user needs more closely. This paper mostly deals with gaining imprecise information from relational database systems. Presented concept is based on fuzzy sets and automatic clustering techniques that allow built membership function and fuzzy queries processing. Implementation of fuzzy logic on database systems extends traditional SQL language with new mechanisms and new features, so the existing relational database systems will be more flexible, queries more intelligent and similar to ordinary communication methods.