A geometric framework for modelling similarity search

We suggest a geometric framework for modelling similarity search in large and multidimensional data spaces of general nature, formed by the concept of the similarity workload, which is a probability metric space Ω (query domain) with a distinguished finite subspace X (dataset), together with an assembly of concepts, techniques, and results from metric geometry. As some of the latter are being currently reinvented by the database community, it seems desirable to try and bridge the gap between database research and the relevant work already done in geometry and analysis