A system recommending top-k objects for multiple users preferences

What is it about?

We discuss models of user preferences in Web environment. We construct a model for user preference querying over a number of data sources and ordering of answers by a combination of particular attribute rankings. We generalize Fagin's algorithm in two directions - we develop some new heuristics for top-k search in the model without random access and propose a method of ordering lists of objects by user fuzzy function. To enable different user preferences our system does not require objects to be sorted - instead we use a B+- tree on each of the attribute domains. This leads to a more realistic model of Web services. We implement our methods and heuristics for search of top-k answers into Tokaf middleware framework prototype. We describe experiments with Tokaf and compare different performance measures with some other methods.

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