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ICDE
2003
IEEE

Scaling up the ALIAS Duplicate Elimination System

14 years 5 months ago
Scaling up the ALIAS Duplicate Elimination System
Duplicate elimination is an important stage in integrating data from multiple sources. The challenges involved are finding a robust deduplication function that can identify when two records are duplicates and efficiently applying the function on very large lists of records. In ALIAS the task of designing a deduplication function is eased by learning the function from examples of duplicates and nonduplicates and by using active learning to spot such examples effectively [1]. Here we investigate the issues involved in efficiently applying the learnt deduplication system on large lists of records. We demonstrate the working of the ALIAS evaluation engine and highlight the optimizations it uses to significantly cut down the number of record pairs that need to be explicitly materialized.
Sunita Sarawagi, Alok Kirpal
Added 01 Nov 2009
Updated 01 Nov 2009
Type Conference
Year 2003
Where ICDE
Authors Sunita Sarawagi, Alok Kirpal
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