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Data ambiguity is inherent in applications such as data integration, location-based services, and sensor monitoring. In many situations, it is possible to "Clean", or remove, ambiguities from these databases. For example, the GPS location of a user is inexact due to measurement errors, but context information (e.g., what a user is doing) can be used to reduce the imprecision of the location value. In order to obtain a database with a higher quality, the authors study how to disambiguate a database by appropriately selecting candidates to clean. This problem is challenging because cleaning involves a cost, is limited by a budget, may fail, and may not remove all ambiguities.
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