Prof. Dr. Ralph Bergmann is full professor (C4) at the University of Trier and is directing a research group on Business Information Systems. He studied computer science and electrical engineering and received a doctoral degree as well as a habilitation degree in computer science from the University of Kaiserslautern. He has over 17 years experience as researcher at the Universities of Kaiserslautern, Hildesheim, and Trier and led more than 25 funded national and European research and development projects. He is author and co-author of more than 140 scientific papers and four books.

AG 1, AG 3, AG 5, RG2, AG 2, AG 4, RG1, SWS   Info

AG Audience

English

60 Minutes

Saarbrücken

Product recommendation requires a substantial amount of knowledge and experience about products, customers, and communication strategies. Hence, virtual shopping assistants need to explicitly represent and process such knowledge to make recommendations of products by intelligently considering the customer’s wishes. Further, customers’ wishes are usually vague and imprecise and they can often not be fulfilled exactly by an available product. Therefore, knowledge-based methods for product recommendation must be able to determine approximate solutions, i.e. recommendations of products which fulfil the customer’s needs as well as possible. This is particularly a difficult task for complex products that can be customized according to the user’s needs. In this talk I will present a compilation of recent results addressing these questions, which have their origin in case-based reasoning and similarity-based search.

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