RWTH Aachen University
In the era of huge datasets, the top-k search becomes an effective way to decrease the search time of top-k objects. The original top-k search requires a monotone combination function and lists of objects ordered by attribute values. The authors' approach of the top-k search is motivated by complex user preferences over product catalogues. Such user preferences are composed of the local user preferences of the attributes' values (user defined arbitrary fuzzy functions, one for each attribute) and a user defined monotone combination function. This paper compares two different approaches of the top-k search for this type of non-monotone query.