Metric access methods (MAMs) serve as a tool for speeding similarity queries. However, all MAMs developed so far are index-based; they need to build an index on a given database. T...
In this paper we present a scalable and distributed access structure for similarity search in metric spaces. The approach is based on the Content– addressable Network (CAN) parad...
We researched to try to find a way to reduce the cost of nearest neighbor searches in metric spaces. Many similarity search indexes recursively divide a region into subregions by u...
So far, an efficient similarity search in multimedia databases has been carried out by metric access methods (MAMs), where the utilized similarity measure had to satisfy the metric...
Similarity search is a fundamental operation for applications that deal with unstructured data sources. In this paper we propose a new pivot-based method for similarity search, ca...