Publication at Faculty of Mathematics and Physics |
2020
Abstract
The TriGen algorithm is a general approach to transform distance spaces in order to provide both exact and approximate similarity search in metric and non-metric spaces. This paper focuses on the reduction of intrinsic dimensionality using TriGen.
Besides the well-known intrinsic dimensionality based on distance distribution, we inspect properties of triangles used in metric indexing (the triangularity) as well as properties of quadrilaterals used in ptolemaic indexing (the ptolemaicity). We also show how LAESA with triangle and ptolemaic filtering behaves on several datasets with respect to the proposed indicators.