Learning the users' preferences in e-commerce: A weight-adjustment approach

Issue title: Soft Computing and its Applications to E-Business

Article type: Research Article

Authors: Prasad, Bhanu

Affiliations: Department of Computer and Information Sciences, Florida A&M University, Tallahassee, FL 32307, USA. E-mail: bhanu.prasad@famu.edu

Abstract: Learning the preferences of users is an important problem in e-commerce research. This paper presents a system for that purpose, and it is primarily based on weight vectors. Learning is incorporated in the form of refining the weights. The system is sensitive to the users' change of trend and is implemented for labor profile domain. An empirical evaluation has been conducted in a simulated environment. The results proved the following: (1) The system converges if the user populations have some common preferences, (2) The system detects and adapts to a change of trend, and (3) It takes more time to converge in the case of more weights.

DOI: 10.3233/KES-2004-8404

Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 8, no. 4, pp. 205-211, 2004