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Optimizing Semantic Reasoning on Memory-Constrained Platforms using the RETE Algorithm
Published on Jul 10, 2018510 Views
Mobile hardware improvements have opened the door for deploying rule systems on ubiquitous, mobile platforms. By executing rule-based tasks locally, less re-mote (cloud) resources are needed, bandwidt
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Optimizing Semantic Reasoning on Memory-Constrained Platforms using the RETE Algorithm00:00
Context: clinical guidelines & decision support00:26
Context: clinical guidelines & decision support02:16
Context: Patient Self-Management03:39
Context: Patient Self-Management (2)04:05
Rule-based reasoning on mobile platforms?05:53
How about ontology-based reasoning?07:25
Optimizing usage of OWL2 RL ruleset09:20
Optimizing the RETE algorithm for OWL2 RL11:50
Issues with OWL2RL + RETE?14:35
Proposed solution: RETEpool15:46
RETEpool issues17:47
Benchmark setup19:10
Benchmark setup (2)20:34
Benchmark results21:13
Benchmark results | (S.i): introduce separate memory pool - 122:28
Benchmark results | (S.i): introduce separate memory pool - 222:37
Benchmark results | (S.i): introduce separate memory pool - 322:50
Benchmark results | (S.i): introduce separate memory pool - 423:05
Benchmark results | (S.i): introduce separate memory pool - 523:19
Benchmark results | (S.i): introduce separate memory pool - 623:27
Benchmark results | (S.i): introduce separate memory pool - 723:49
Benchmark results | (S.ii): re-use existing RDF store - 124:19
Benchmark results | (S.ii): re-use existing RDF store - 225:11
(Future) work (in progress) (2) - 126:46
(Future) work (in progress) (2) - 227:51