Author:
Gérard Kubryk
Affiliation:
Laboratoire I3S/CNRS in Sophia Antipolis, France
Keyword(s):
Web and audio services, requirements analysis, adaptative and customized menus, models and methods specifications, machine learning.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Enterprise Information Systems
;
Functional and Non-Functional Requirements
;
Human Factors
;
Human-Computer Interaction
;
Intelligent User Interfaces
;
Physiological Computing Systems
;
User Needs
Abstract:
Web engineering becomes increasingly important in the last years. WEB and audio services have to provide the best services possible. To achieve this goal, they have to find out what the customers are doing without altering their privacy. This paper presents two classes of models, mathematical and learning models, and two possible ways to manage and build adaptative menus. These methods are gravity analogy, learning by sanction reinforcement. Later on, a comparison of these two models will be made based on two criteria: efficiency (answering time and computer load) and accuracy with customer expectation. The final step will be to carry out psychological analysis of user activity, meaning, “what is my perception of time into and between service consultation” to determine ways to set parameters of such a system.