Abstract
Preferences are an important natural concept in real life and are well-known in the database and artificial intelligence community. Modeling preferences as strict partial orders closely matches people’s intuition. There are many algorithms for the evaluation of these strict partial orders. In particular some algorithms rely on the total order or the lattice structure constructed by a preference query. This paper provides an overview of the structure of preference orders. We present several measures of the different “better-than graphs” and give a deep insight into the structure of preferences. In fact, a careful analysis of the underlying “better-than graph” enables one to develop efficient algorithms for preference computation.
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