Searching in metric spaces with user-defined and approximate distances

Metric access methods (MAMs), such as the M-tree, are powerful index structures for supporting ty queries on metric spaces, which represent a common abstraction for those searching problems that arise in many modern application areas, such as multimedia, data mining, decision support, pattern recognition, and genomic databases. As compared to multi-dimensional (spatial) access methods (SAMs), MAMs are more general, yet they are reputed to lose in flexibility, since it is commonly deemed that they can only answer queries using the same distance function used to build the index. In this paper we show that this limitation is only apparent

• Type: Journal
• Year: 2002
• Where: TODS
• Authors: Paolo Ciaccia, Marco Patella
• Keywords: Access Method, Distance Functions, Index Structure, TODS 2002