Use of Fuzzy Sets in Semantic Nets for Providing On-Line Assistance to User of Technological Systems

TL;DR

This paper introduces a fuzzy set-based semantic network model for AI systems to provide online assistance by handling uncertain user queries in technological systems like word processors.

Contribution

It develops a novel semantic network structure integrating fuzzy sets to model uncertain user knowledge and improve online assistance in AI systems.

Findings

Fuzzy semantic networks effectively model uncertain user knowledge.

The method improves diagnosis of fuzzy user queries.

Enhanced online assistance in technological systems.

Abstract

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.