SGDB - Simple graph database optimized for activation spreading computation
|SGDB - Simple graph database optimized for activation spreading computation|
|Author(s)||Ciglan M., Norvag K.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||Unknown (Extra: Activation algorithm, Execution time, Graph database, Graph queries, Large graphs, Performance characteristics, Pilot applications, Preloading, Storage media, Storage model, Wikipedia, Optimization, Technical presentations, Database systems)|
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SGDB - Simple graph database optimized for activation spreading computation is a 2010 conference paper written in English by Ciglan M., Norvag K. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
In this paper, we present SGDB, a graph database with a storage model optimized for computation of Spreading Activation (SA) queries. The primary goal of the system is to minimize the execution time of spreading activation algorithm over large graph structures stored on a persistent media; without pre-loading the whole graph into the memory. We propose a storage model aiming to minimize number of accesses to the storage media during execution of SA and we propose a graph query type for the activation spreading operation. Finally, we present the implementation and its performance characteristics in scope of our pilot application that uses the activation spreading over the Wikipedia link graph.
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