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A Preference-Aware Query Model for Data Web Services
A Preference-Aware Query Model for Data Web Services
International audience; Data Mashup is a special class of applications mashup thatcombines data elements from multiple data sources (that are often ex-ported as data web services) to respond to transient business needs onthe y. In this paper, we propose a semantic model for data servicesalong with a declarative approach for creating data mashups withoutany programming involved. Given a query formulated over domain on-tologies, and a set of preferences modeled using the fuzzy set theory,our approach selects the relevant data services based on their semanticmodeling using an RDF query rewriting algorithm. Selected services arethen orchestrated using a ranking-aware algebra to rank their returnedresults based on users preferences at the data mashup execution time.
- Lyon College United States
- University of Carthage Tunisia
- Université Paris Diderot France
Microsoft Academic Graph classification: Data Web Web search query RDF query language computer.programming_language computer Data as a service Mashup computer.software_genre Set (abstract data type) Semantic data model Rank (computer programming) Computer science Database
[INFO]Computer Science [cs], [INFO] Computer Science [cs]
[INFO]Computer Science [cs], [INFO] Computer Science [cs]
Microsoft Academic Graph classification: Data Web Web search query RDF query language computer.programming_language computer Data as a service Mashup computer.software_genre Set (abstract data type) Semantic data model Rank (computer programming) Computer science Database
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).1 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).1 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!
- Lyon College United States
- University of Carthage Tunisia
- Université Paris Diderot France
International audience; Data Mashup is a special class of applications mashup thatcombines data elements from multiple data sources (that are often ex-ported as data web services) to respond to transient business needs onthe y. In this paper, we propose a semantic model for data servicesalong with a declarative approach for creating data mashups withoutany programming involved. Given a query formulated over domain on-tologies, and a set of preferences modeled using the fuzzy set theory,our approach selects the relevant data services based on their semanticmodeling using an RDF query rewriting algorithm. Selected services arethen orchestrated using a ranking-aware algebra to rank their returnedresults based on users preferences at the data mashup execution time.