Authors:
Anastasios Savvopoulos
and
Maria Virvou
Affiliation:
University of Piraeus, Greece
Keyword(s):
User modelling server, e-Commerce, m-Commerce, Adaptivity, Clustering, Stereotypes.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Computational Intelligence
;
Evolutionary Computing
;
Expert Systems
;
Health Information Systems
;
Knowledge Discovery and Information Retrieval
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Machine Learning
;
Soft Computing
;
Symbolic Systems
Abstract:
Recommending applications are used by many researchers as the main means of achieving personalization. However, the difficulty is to apply the same recommender and personalization techniques to a totally different system that belongs to a different domain and uses a different medium. Furthermore the difficulty level rises when we want to apply the previous recommendation techniques without changing major components or process attributes. In this paper we propose a server that can be used to achieve personalization to a product recommending system. The main advantage of this server is that works both for e-commerce and mobile commerce. We present a case study that we incorporated the user modelling server, which is a mobile e-shop, and discuss within the case the obstacles and breakthroughs we have achieved. The case study clearly shows that the same user modelling server can enhance e-shop application behaviour towards adaptivity and customer personalization.