  Flexible querying of DB allows to extend DBMS in order to support imprecision
and flexibility in queries. Flexible queries use vague and imprecise terms
which have been defined as fuzzy sets. However, there is no consensus on
memberships functions generation. Most of the proposed methods require expert
intervention. This thesis is devised in two parts. In the first part, we
propose a clustering based approach for automatic and incremental membership
functions generation. We have proposed the clustering method CLUSTERDB* which
evaluates clustering quality underway clusters generation. Moreover, we propose
incremental updates of partitions and membership functions after insertion or
deletion of a new object. The second part of this thesis uses these functions
and Formal Concepts Analysis in flexible and cooperative querying. In case of
empty answers, we formally detect the failure reasons and we generate
approximative queries with their answers. These queries help the user to
formulate new queries having answers. The different proposed approaches are
implemented and experimented with several databases. The experimentation
results are encouraging.

Databases