Postprint version. Published in 2010 Fifth International Conference on Digital Information Management (ICDIM), July 5-8, 2010, Thunder Bay, ON, Canada, July 1, 2010, pages 384-391.
NOTE: At the time of publication, the author Lubomir Stanchev was not yet affiliated with Cal Poly.
The definitive version is available at https://doi.org/10.1109/ICDIM.2010.5664256.
In this paper we explore the properties of description indices that store concept descriptions rather than plain data. Although these novel data structures are beneficial for efficiently answering semantic web queries, expressed in a language such as nRQL or SPARQL-DL, they take extra storage and their maintenance can become a performance bottleneck. In order to alleviate these shortcomings, we introduce a procedure for merging description indices. Experimental results over the LUBM benchmark show that this technique can result in economy of storage space, while the performance is slightly affected for a static workload and is improved for a dynamic workload.
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