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Arnold: Declarative Crowd-Machine Data Integration

Arnold: Declarative Crowd-Machine Data Integration

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We have developed a declarative approach to data cleaning and integration that balances when and where to apply crowd-sourcing and machine computation using a new type of data independence that we term Labor Independence. Labor Independence divides the logical operations that should be performed on each record from the physical implementations of those operations. Using this layer of independence,the data cleaning process can choose the physical operator for each logical operation that yields the highest quality for the lowest cost. We introduce Arnold, a data cleaning and integration architecture that utilizes Labor Independence to efficiently clean and integrate large amounts of data.
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