Use of Fuzzy Sets in Semantic Nets for Providing On-Line Assistance to User of Technological Systems
This work addresses the challenge of assisting novice users with uncertain knowledge in interacting with technological systems, representing an incremental improvement by integrating fuzzy sets into semantic networks.
The paper tackles the problem of providing effective on-line assistance to users of technological systems by developing a new semantic network structure based on fuzzy sets theory, applied to a word processor software, and proposes a method to measure similarity between fuzzy linguistic variables for easier diagnosis of user queries.
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.