A geometric framework for modelling similarity search

Author

Pestov, Vladimir

Author_Institution

Sch. of Math. & Comput. Sci., Victoria Univ., Wellington, New Zealand

fYear

1999

fDate

1999

Firstpage

150

Lastpage

154

Abstract

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

Keywords

image retrieval; probability; search problems; solid modelling; database community; database research; dataset; finite subspace; geometric framework; metric geometry; multidimensional data spaces; probability metric space; query domain; similarity search modelling; similarity workload; Bridges; Character generation; Extraterrestrial measurements; Information geometry; Laboratories; Multidimensional systems; Read only memory; Solid modeling; Spatial databases; Tellurium;

fLanguage

English

Publisher

ieee

Conference_Titel

Database and Expert Systems Applications, 1999. Proceedings. Tenth International Workshop on

Conference_Location

Florence

Print_ISBN

0-7695-0281-4

Type

conf

DOI

10.1109/DEXA.1999.795158

Filename

795158