Finding Preferred Objects with Taxonomies

Preferences about objects of interest are often expressed at different levels of granularity, not always matching the level of detail of stored data. For instance, we prefer rock to pop music, yet scheduled concerts only cite the name of the performer, with no reference to the musical genre. In this paper we address this common mismatch by leveraging the vast amounts of data organized in taxonomies (such as those found in electronic catalogs and classification systems) for propagating preferences from more generic to more specific concepts. This will help users to locate their preferred objects. In spite of its apparent simplicity, this problem requires special care in order to avoid some undesirable effects, e.g., when conflicting preferences at different levels have to be combined (although, generally, we prefer rock to pop music, we would never miss a performance by Madonna). We present a formal model to represent preferences and state the desirable properties of preference propagation, such as the fact that more specific preferences always prevail over more generic ones. We then propose a method for propagating preferences along taxonomies, complying with the stated properties, and show how preferred objects can thereby be efficiently determined.