Scaling up the ALIAS duplicate elimination system : a demonstration
DSpace at IIT Bombay
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Title |
Scaling up the ALIAS duplicate elimination system : a demonstration
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Creator |
SARAWAGI, S
KIRPAL, A |
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Description |
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 non-duplicates 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.
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Publisher |
IEEE
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Date |
2011-10-24T14:16:07Z
2011-12-15T09:11:39Z 2011-10-24T14:16:07Z 2011-12-15T09:11:39Z 2003 |
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Type |
Proceedings Paper
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Identifier |
19TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING, PROCEEDINGS,783-785
0-7803-7665-X 1063-6382 http://dx.doi.org/10.1109/ICDE.2003.1260867 http://dspace.library.iitb.ac.in/xmlui/handle/10054/15440 http://hdl.handle.net/100/2202 |
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Source |
19th International Conference on Data Engineering,BANGALORE, INDIA,MAR 05-08, 2003
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Language |
English
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