Metric Space Searching based on Random Bisectors and Binary Fingerprints
José María Andrade,
César Alejandro Astudillo and
Rodrigo Paredes
We present a novel index for approximate searching in metric spaces based
on random bisectors and binary fingerprints.
The aim is to deal with scenarios where the main memory available is small.
The method was tested
on synthetic and real-world metric spaces.
Our results show that our scheme outperforms the standard
permutant-based index in
scenarios where memory is scarce.