Probabilistic skyline queries

The ability to deal with uncertain information is becoming increasingly important for modern database applications. Whereas a conventional (certain) object is usually represented by a vector from a multidimensional feature space, an uncertain object is represented by a multivariate probability density function (PDF). This PDF can be defined either discretely (e.g. by a histogram) or continuously in parametric form (e.g. by a Gaussian Mixture Model). For a database of uncertain objects, the users expect similar data analysis techniques as for a conventional database of certain objects. An important analysis technique for certain objects is the skyline operator which finds maximal or minimal vectors with respect to any possible attribute weighting. In this paper, we propose the concept of probabilistic skylines, an extension of the skyline operator for uncertain objects. In addition, we propose efficient and effective methods for determining the probabilistic skyline of uncertain obj...

• Type: Conference
• Year: 2009
• Where: CIKM
• Authors: Christian Böhm, Frank Fiedler, Annahita Oswald, Claudia Plant, Bianca Wackersreuther
• Keywords: CIKM 2009, Gaussian Mixture Model, Probabilistic Skyline, Uncertain Objects