ISeller: A flexible personalization infrastructure for E-commerce applications

Abstract

We present ISeller, an industrial-strength recommendation system for a diverse range of commercial application domains. The system supports several recommendation paradigms such as collaborative, content-based and knowledge-based filtering, as well as one-shot and conversational interaction modes out of the box. A generic user modeling component allows different forms of hybrid personalization and enables the system to support process-oriented interactive selling in various product domains. This paper contributes a detailed discussion of a domain independent and flexible recommendation system from a software architecture viewpoint and illustrates it with different usage scenarios. © 2009 Springer Berlin Heidelberg.