Using Large Databases and Self-Organizing Maps without tears

Nowadays the need to process lots of complex multimedia databases is more frequent. Recent investigations such as MAM-SOM* and SAM-SOM* families propose the combination of self-organising maps (SOM) with access methods for a faster similarity information retrieval. In this investigation we present experimental results using recent access methods such as slim-tree and omni-sequential that show the improvement acquired by these techniques and their properties in contrast with a traditional SOM network observing up to 90% of performance improvement.