Abstract
Personalization, information filtering and recommendation are key techniques helping online-customers to orientate themselves in e-commerce environments. Similarity is an important underlying concept for the above techniques. Depending on the representation mechanism of information items different similarity approaches have been established in the fields of information retrieval and case-based reasoning. However, many times product descriptions consist of both, structured attribute value pairs and free-text descriptions. Therefore, we present a hybrid similarity approach from information retrieval and case-based recommendation systems and enrich it with additional knowledge-based concepts like threshold values and explanations. Furthermore, we implemented our hybrid similarity concept in a service component and give evaluation results for the e-tourism domain.
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Zanker, M., Gordea, S., Jessenitschnig, M., Schnabl, M. (2006). A Hybrid Similarity Concept for Browsing Semi-structured Product Items. In: Bauknecht, K., Pröll, B., Werthner, H. (eds) E-Commerce and Web Technologies. EC-Web 2006. Lecture Notes in Computer Science, vol 4082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11823865_3
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DOI: https://doi.org/10.1007/11823865_3
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