Abstract
In the last decade there has been much interest in preference query processing for various applications like personalized information or decision making systems. Preference queries aim to find only those objects that are most preferred by the user. However, the underlying data set may contain NULL values which represent unknown or incomplete data. Most of the existing algorithms for preference query evaluation do not know how to treat these NULL values and consider them worse than any other value. Other algorithms do not allow NULLs in their input data set. However, NULL values are common in data sets and must be considered in preference query evaluation. In this paper we introduce an approach to handle NULL values in preference queries which extends preference algebra, a formal model for preference specification. Our approach can be adopted by all preference query algorithms which rely on strict partial orders, because it does not violate the transitivity relation as other methods do.
Authors
Markus Endres, Patrick Roocks, Florian Wenzel, Alfons Huhn, Werner Kießling
Publication
Proceedings of the 6th Multidisciplinary Workshop on Advances in Preference Handling in conjunction with ECAI 2012, Montpellier, France, August 2012