ISELLER -- A GENERIC AND HYBRID RECOMMENDATION SYSTEM FOR INTERACTIVE SELLING SCENARIOS

We present ISeller an industry-strength recommendation system for online shopping platforms. The system supports several recommendation paradigms like collaborative, content-based and knowledge-based filtering as well as one-shot and conversational interaction modes. A generic user modelling component allows different forms of hybrid reasoning strategies as well as enables the system to support a process-oriented way of interactive selling in various product domains. This application paper contributes a comprehensive scenario for interactive selling on commercial platforms and thus motivates central user modelling services for recommendation systems. Furthermore, we give an outline on the technical architecture and the implemented system. Our presentation will be illustrated with actually fielded examples from domains of luxury-articles like coffee and cigars