Genetic algorithm and fuzzy logic based flexible querying in databases

Databases are very important sources for storing huge size of data. Today, yearly produced information is expressed as multiple size of it, which produced before. Retrieving correct data is as important as storing. At this point, querying becomes more important. Classical SQL queries return a record only if the database has a record which satisfies all search criteria. However, the user mostly wants to see similar records when there is no record satisfying all search criteria. For this reason, studies are focused on flexible SQL queries. In this sense, fuzzy logic, which is an artificial intelligent technique, is becoming more important since it maintains the idea that there may be interval values between true and false, contrary to the logic of Aristotle. Genetic algorithm based database querying is another flexible querying approach to the mentioned problem. In this thesis, both approaches are applied on a sample real-estate database and the results are compared while discussing the efficiency of the two methods.