Abstract
As long as there have been database search engines there has been the problem of what to present to the user when there is no perfect match and how to present that query result to the user. Respecting the user’s search preferences is the suitable way to search for best matching alternatives. Modelling such preferences as strict partial orders in “A is better than B” semantics has been proven to be user intuitive in various internet applications. The better the search result, the better is the psychological advantage of the presenter. Thus, there is the necessity to know the quality of the search result with respect to the search preferences. This chapter introduces a novel personalized and situated quality assessment for query results. Based on a human comprehensible linguistic model of five quality categories a very intuitive framework for valuations is defined for numerical as well as for categorical search preferences. These quality valuations provide human comprehensible presentation arguments. Moreover, they are used to compute the situated overall quality of a search result. For delivery of the results a flexible and situated fillter decides which results to present, e.g. by respecting quality requirements of the user. A so called presentation preference determines which results are predestined to be especially pointed out to a user. Eventually, it will be evaluated how ecommerce applications will profit from the use of a preference based search in combination with the introduced human comprehensible quality assessment. Considering the procurement of goods via internet the idea is simple. A customer expects to have at least the service he or she has when directly contacting a human sales person. That means the customer wants to be treated individually according to his or her needs. But the misery already begins with the first step, the usage of the search engine.
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Fischer, S., Kießling, W., Preisinger, T. (2006). Preference based Quality Assessment and Presentation of Query Results. In: Bordogna, G., Psaila, G. (eds) Flexible Databases Supporting Imprecision and Uncertainty. Studies in Fuzziness and Soft Computing, vol 203. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33289-8_4
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DOI: https://doi.org/10.1007/3-540-33289-8_4
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