Data Fusion
Originally developed for signal processing but an entirely general approach:
- Improved performance can be obtained by combing evidence from several different sources
When used for similarity searching
- Do a similarity search for a target structure and then rank the database structures in order of decreasing similarity
- Repeat with different representations, coefficients, etc.
- Add the rank positions for a given structure to give an overall fused rank position
- The resulting fused ranking is the output from the search
- Small, but consistent, improvements in performance over use of a single ranking