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Overview: This paper presents the design and implementation of BRAHMS, an efficient RDF storage system, specifically designed to support fast semantic association discovery in large RDF bases. The paper presents memory usage and timing results of several tests performed with BRAHMS and compare them to similar tests performed using Jena, Sesame, and Redland, three of the well-known RDF storage systems. Results show that BRAHMS handles basic association discovery well, while the RDF query languages and even the low-level APIs in the other three tested systems are not suitable for the implementation of semantic association discovery algorithms.
Expediting the VMware Upgrade Process with vWire
Download this whitepaper by VMware Certified Professional Dominic Rivera and follow along as he walks through upgrading to VMware vSphere 4.0 with vWire...
Data Protection Strategies Using Replication
This paper examines four data protection strategies and compares their merits for the most common business continuance scenarios.
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