Debugging user interface descriptions of knowledge-based recommender applications
Proceedings of the 11th international conference on Intelligent user interfaces
Reducing development and maintenance efforts for web-based recommender applications
International Journal of Web Engineering and Technology
International Journal of Learning Technology
Knowledge-Based Recommendation: Technologies and Experiences from Projects
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Automated debugging of recommender user interface descriptions
Applied Intelligence
Proceedings of the 4th International Conference on Uniquitous Information Management and Communication
Diagnosing faulty transitions in recommender user interface descriptions
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
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The increasing complexity of products and services offered by online stores and electronic marketplaces makes the identification of appropriate solutions a challenging task. Customers can differ greatly in their expertise and level of knowledge w.r.t. such product assortments. Consequently, intelligent sales assistance systems are required which support customers with intuitive and personalized dialogs. Knowledge-based recommender systems meet these requirements by allowing a flexible mapping of product, marketing and sales knowledge to the formal representation of a knowledge base. This paper presents the domain-independent knowledge-based recommender system Koba4MS which assists customers and sales representatives by guaranteeing the consistency and appropriateness of proposed solutions, identifying additional selling opportunities and by providing intelligent explanations for identified results. Using examples from the financial services domain we show how constraint satisfaction, model-based diagnosis, personalization and intuitive knowledge acquisition techniques support the effective implementation of customer-oriented sales dialogs. Finally, we present experiences gained from commercial projects.