1. Authors
2. Abstract
3. Test data
4. Experiments
5. Related Work

Sven Puhlmann, Melanie Weis and Felix Naumann

Detecting duplicates is a problem with a long tradition in many domains, such as customer relationship management and data warehousing. The problem is twofold: First define a suitable similarity measure, and second efficiently apply the measure to all pairs of objects. With the advent and pervasion of the XML data model, it is necessary to find new similarity measures and to develop efficient methods to detect duplicate elements in nested XML data.

A classical approach to duplicate detection in flat relational data is the sorted neighborhood method, which draws its efficiency from sliding a window over the relation and comparing only tuples within that window. We extend the algorithm to cover not only a single relation but nested XML elements. To compare objects we make use of XML parent and child relationships. For efficiency, we apply the windowing technique in a bottom-up fashion, detecting duplicates at each level of the XML hierarchy. Experiments show a speedup comparable to the original method data and they show the high effectiveness of our algorithm in detecting XML duplicates. [more]

Here you find the link to the journal:
http://www.springerlink.com/content/r36h65n680871870/

• Dataset 1
  • ToXgene
  • Dirty XML Data Generator
• Dataset 2
• Dataset 3

Here you find several scientific work which also deal with Duplicate Detection in XML data:

• A Duplicate Detection Benchmark for XML (and Relational) Data

• Detecting Duplicate Objects in XML Documents
  
• DogmatiX Tracks down Duplicates in XML
• Fuzzy Duplicate Detection on XML Data