C-SWRL: SWRL for Reasoning over Stream Data
| Autor: | Edmond Jajaga, Lule Ahmedi |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Information retrieval
Computer science Data stream mining Aggregate (data warehouse) Inference 02 engineering and technology computer.file_format 020204 information systems 0202 electrical engineering electronic engineering information engineering Semantic technology 020201 artificial intelligence & image processing RDF Open-world assumption Semantic Web computer De facto standard |
| Zdroj: | ICSC |
| Popis: | Semantic technologies have been extensively used for integrating stream data applications. However, using SWRL, which has become the de facto standard rule language in Semantic Web, has never been used in stream data applications. Its open world assumption and monotonic nature makes SWRL powerless for doing continuous inference over stream data. For example, using aggregate functions on a particular window of streams cannot be expressed in SWRL. C-SPARQL is a framework which supports continuous querying over data streams. We introduce here C-SWRL, a unified Semantic Web stream reasoning system that further supports continuous reasoning over stream data. C-SWRL utilizes C-SPARQL filtering and aggregation of RDF streams to enable closed-world and time-aware reasoning with SWRL rules. Moreover, the non-monotonic behavior is supported with the use of OWLAPI constructs. The system is presented by means of examples in water quality monitoring. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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