Sciweavers

Share
DEXAW
1999
IEEE

Using the Distance Distribution for Approximate Similarity Queries in High-Dimensional Metric Spaces

9 years 8 months ago
Using the Distance Distribution for Approximate Similarity Queries in High-Dimensional Metric Spaces
We investigate the problem of approximate similarity (nearest neighbor) search in high-dimensional metric spaces, and describe how the distance distribution of the query object can be exploited so as to provide probabilistic guarantees on the quality of the result. This leads to a new paradigm for similarity search, called PAC-NN (probably approximately correct nearest neighbor) queries, aiming to break the "dimensionality curse". PAC-NN queries return, with probability at least 1 ; , a (1 + )-approximate NN
Paolo Ciaccia, Marco Patella
Added 03 Aug 2010
Updated 03 Aug 2010
Type Conference
Year 1999
Where DEXAW
Authors Paolo Ciaccia, Marco Patella
Comments (0)
books