Abstract
We present a parametric framework (UFleSe) with a user-friendly interface having a search engine that enables regular users (without the need of neither technical nor theoretical knowledge) to define their fuzzy concepts, rules, similarity relations, synonyms, antonyms, and personalizing their definitions for different users, and to link them with the crisp database fields for performing flexible, expressive queries in a language close to natural language. It works over multiple modern and conventional data formats, such as JSON, SQL, Prolog, CSV, XLS, and XLSX. We present the syntax involved in the construction of our various flexible searching criteria and their personalizations. Furthermore, we present the architecture of this novel system that combines fuzzy, crisp data, and similarity relations in its queries to return constructive answers ordered by a degree of searching criteria satisfaction (truth-value between 0 and 1). Finally, we include a comparative analysis of different fuzzy querying systems here, and we provide various experiments, to show the system behavior, performance, efficiency, and scalability as well.
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