Introducing specialization in e-commerce recommender systems. (September 2013)

• Record Type: Journal Article
• Authors: Palopoli, Luigi; Rosaci, Domenico; Sarnè, Giuseppe ML
• Other Names: Fortino Giancarlo guest-editor.
• Is Part Of: Concurrent engineering, research and applications. Volume 21:Number 3(2013)
• Page Start: 187
• Page End: 196
• Publication Date: 2013-09
• Subjects: Recommender systems -- multi-agent systems -- distributed architectures -- e-commerce -- consumer buying behavior; Production engineering -- Periodicals; Concurrent engineering -- Periodicals; 621.39
• DOI: 10.1177/1063293X13493915
• Languages: English
• ISSNs: 1063-293X

Abstract

Currently, customers' trading activities are supported by recommender tools that are able to generate personalized suggestions. Many of these recommenders are centralized, lacking in efficiency and scalability, while others are distributed and, conversely, imply a computational overhead on the client side being often excessive or even unacceptable for many devices. In this article, we propose a distributed recommender, based on a multi-tiered agent system, where the agents of each tier are specialized in a different e-commerce activity. The proposed system is capable of generating effective suggestions without a too onerous computational burden. In particular, we show that our system introduces significant advantages in terms of openness, privacy, and security.