Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.741622
Title: Incremental rule-based reasoning on semantic data streams
Author: Albeladi, Rehab
ISNI:       0000 0004 7224 8849
Awarding Body: University of Southampton
Current Institution: University of Southampton
Date of Award: 2016
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Abstract:
This thesis investigates the area of semantic stream processing, in which data streams are combined with semantic reasoning techniques. We have investigated techniques for rule-based reasoning over semantic streams in which reasoning is implemented natively over streams as data flow networks, and have developed an adaptive optimisation method to cope with the changing nature of streams. The contributions of this thesis include R4, a native rule-based reasoner for RDF streams using the Rete algorithm, and a cost-based adaptive plan optimiser designed for RDF streams. We have evaluated the performance of R4 and compared it to both a typical static reasoner and to the state-of-the-art in stream reasoners. The results show that R4 significantly outperforms these reasoners in terms of throughput. We have also evaluated the adaptive optimisation technique, with results that show the ability of the optimiser to devise and adopt better performing plans at runtime.
Supervisor: Gibbins, Nicholas Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.741622  DOI: Not available
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