DocumentCode :
1627989
Title :
Detecting Duplicates in Complex XML Data
Author :
Weis, Melanie ; Naumann, Felix
Author_Institution :
Humboldt-Universitat zu Berlin
fYear :
2006
Firstpage :
109
Lastpage :
109
Abstract :
Recent work both in the relational and the XML world have shown that the efficacy and efficiency of duplicate detection is enhanced by regarding relationships between entities. However, most approaches for XML data rely on 1:n parent/child relationships, and do not apply to XML data that represents m:n relationships. We present a novel comparison strategy, which performs duplicate detection effectively for all kinds of parent/child relationships, given dependencies between different XML elements. Due to cyclic dependencies, it is possible that a pairwise classification is performed more than once, which compromises efficiency. We propose an order that reduces the number of such reclassifications and apply it to two algorithms. The first algorithm performs reclassifications, and efficiency is increased by using the order reducing the number of reclassifications. The second algorithm does not perform a comparison more than once, and the order is used to miss few reclassifications and hence few potential duplicates.
Keywords :
Clustering algorithms; Customer relationship management; Data models; Data warehouses; Detection algorithms; Information management; Motion pictures; Object detection; Partitioning algorithms; XML;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering, 2006. ICDE '06. Proceedings of the 22nd International Conference on
Print_ISBN :
0-7695-2570-9
Type :
conf
DOI :
10.1109/ICDE.2006.49
Filename :
1617477
Link To Document :
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