Efficient and Effective Duplicate Detection in Hierarchical Data
Authors:
- L. LeitãoLLL. Leitão
- 19 March 2012
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Knowledge and Data Engineering
- Vol. 25 (5) , 1028-1041
Abstract
Although there is a long line of work on identifying duplicates in relational data, only a few solutions focus on duplicate detection in more complex hierarchical structures, like XML data. In this paper, we present a novel method for XML duplicate detection, called XMLDup. XMLDup uses a Bayesian network to determine the probability of two XML elements being duplicates, considering not only the information within the elements, but also the way that information is structured. In addition, to improve the efficiency of the network evaluation, a novel pruning strategy, capable of significant gains over the unoptimized version of the algorithm, is presented. Through experiments, we show that our algorithm is able to achieve high precision and recall scores in several data sets. XMLDup is also able to outperform another state-of-the-art duplicate detection solution, both in terms of efficiency and of effectiveness.Keywords
This publication has 14 references indexed in Scilit:
- Duplicate detection through structure optimization2011
- An Overview of XML Duplicate Detection Algorithms2010
- Matching XML documents in highly dynamic applications2008
- Domain-independent data cleaning via analysis of entity-relationship graphACM Transactions on Database Systems, 2006
- Ranking web objects from multiple communities2006
- Object-level ranking2005
- Finding similar identities among objects from multiple web sources2003
- The merge/purge problem for large databasesACM SIGMOD Record, 1995
- Optimization by Simulated AnnealingScience, 1983
- Measurement of DiversityNature, 1949