Similarity measures for multidimensional data

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Similarity measures for multidimensional data
— How similar are two data-cubes? In other words, the question under consideration is: given two sets of points in a multidimensional hierarchical space, what is the distance value between them? In this paper we explore various distance functions that can be used over multidimensional hierarchical spaces. We organize the discussed functions with respect to the properties of the dimension hierarchies, levels and values. In order to discover which distance functions are more suitable and meaningful to the users, we conducted two user study analysis. The first user study analysis concerns the most preferred distance function between two values of a dimension. The findings of this user study indicate that the functions that seem to fit better the user needs are characterized by the tendency to consider as closest to a point in a multidimensional space, points with the smallest shortest path with respect to the same dimension hierarchy. The second user study aimed in discovering which dis...
Eftychia Baikousi, Georgios Rogkakos, Panos Vassil
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ICDE
Authors Eftychia Baikousi, Georgios Rogkakos, Panos Vassiliadis
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