In the Web database scenario, the records to match are highly query-dependent, since they can only be obtained through online queries. Moreover, they are only a partial and biased portion of all the data in the source Web databases. Consequently, hand-coding or offline-learning approaches are not appropriate for two reasons. First, the full data set is not available beforehand, and therefore, good representative data for training are hard to obtain. Second, and most importantly, even if good representative data are found and labeled for learning, the rules learned on the representatives of a full data set may not work well on a partial and biased part of that data set.
Comments: 7 Pages.
[v1] 2012-08-18 12:28:32
Unique-IP document downloads: 53 times
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.