Abstract

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.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.