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We consider logical provenance in the relational setting, observing that for a class of Select-Project-Join (SPJ) transformations, logical provenance specifications encode minimal provenance.
We consider logical provenance in the relational setting, showing that for a class of Select-Project-Join (SPJ) transformations, logical provenance specifications encode minimal provenance.
In the relational setting, extensions of the relational algebra as well as of SQL-like languages have been proposed and a wide range of fuzzy queries has been made available.
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Building trust requires connections and being embedded in relational set-ups with partners, counterparts, suppliers, buyers, etc. Trust is a component of social capital; it can facilitate exchanges and lowers transaction costs.
I use laboratory experiments to examine the effect of truthful and cheap communication in a relational contracting setting.
Recently, we collected a large relational data set via open-ended survey online.
This gives a total of 45 attributes, corresponding to the main dataset used in our relational Bayesian sets runs.
Moreover, sexual double standards in heterosexual relational schema set up expectations that sexual activity occurs within the context of a committed relationship for women and in all types of relationships for men [ 65].
The quality-aware extensions and features are extremely useful when users need to assess the quality of relational data sets and define quality constraints for acceptable data prior to using candidate data sources in decision support systems and conducting big data analytical tasks.
These constructs are known as interactional workability, relational integration, skill set workability and contextual integration.
The model is defined by four constructs: interactional workability; relational integration; skill set workability and contextual integration.
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