The similarity between two shapes is typically calculated by measuring how well the properties and the spatial organization of the primitives forming the shapes agree. But, when this calculations are done independent from the context, i.e. the whole set of shapes in the experiments, a priori significance to the primitives is assigned, which may cause problematic similarity measures. A possible way of using context information in similarity measure between shape A and shape B is using the category information of shape B in calculations. In this study, shapes are represented as depth-1 shape trees and the dissimilarity between two shapes is computed by using an approximate tree matching algorithm. The category information is created as the union of shape trees that are in the same category and this information guides the matching process between a query shape and a shape whose category is known.