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.
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Jessenitschnig, M., Zanker, M. (2009). ISeller: A Flexible Personalization Infrastructure for e-Commerce Applications. In: Di Noia, T., Buccafurri, F. (eds) E-Commerce and Web Technologies. EC-Web 2009. Lecture Notes in Computer Science, vol 5692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03964-5_31
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DOI: https://doi.org/10.1007/978-3-642-03964-5_31
Publisher Name: Springer, Berlin, Heidelberg
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