  The main objective of this paper is to develop a new semantic Network
structure, based on the fuzzy sets theory, used in Artificial Intelligent
system in order to provide effective on-line assistance to users of new
technological systems. This Semantic Networks is used to describe the knowledge
of an "ideal" expert while fuzzy sets are used both to describe the approximate
and uncertain knowledge of novice users who intervene to match fuzzy labels of
a query with categories from an "ideal" expert. The technical system we
consider is a word processor software, with Objects such as "Word" and Goals
such as "Cut" or "Copy". We suggest to consider the set of the system's Goals
as a set of linguistic variables to which corresponds a set of possible
linguistic values based on the fuzzy set. We consider, therefore, a set of
interpretation's levels for these possible values to which corresponds a set of
membership functions. We also propose a method to measure the similarity degree
between different fuzzy linguistic variables for the partition of the semantic
network in class of similar objects to make easy the diagnosis of the user's
fuzzy queries.
