Eksempler på brug af Big data sources på Engelsk og deres oversættelser til Dansk
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When thinking about big data sources, many researchers immediately focus on online data created and collected by companies,
but cleaning big data sources seems to be more difficult.
There is just too much to be gained by linking survey data to the big data sources discussed in chapter 2.
In other words, even though some big data sources are non-reactive,
In other words, even though some big data sources are nonreactive,
eg. external Big data sources… The list of applications is endless
sometimes the effects of these treatments are captured in always-on big data sources.
Substantive focus Big data source.
In conclusion, Blumenstock's amplified asking approach combined survey data with a big data source to produce estimates comparable to those from a gold-standard survey.
Even though each big data source is distinct,
In enriched asking, survey data builds context around a big data source that contains some important measurements
build a machine learning model that uses the big data source to predict survey answers.
Amplified asking using a predictive model to combine survey data from a few people with a big data source from many people.
In both cases, however, the researchers had to bring interesting questions to the big data source;
look for a big data source from those people that might be used to predict their answer,
Too often, however, researchers seem to treat the size of big data source as an end-"look how much data I can crunch"-rather than a means to some more important scientific objective.
In amplified asking, a researcher uses a predictive model to combine a small amount of survey data with a big data source in order to produce estimates at a scale
In enriched asking, a big data source contains some important measurements
The three sources of drift mean that any pattern in a big data source could be caused by an important change in the world,
researchers using this approach need to be especially concerned about possible biases caused by who is included-and who is not included-in their big data source.