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2005
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Merging Interface Schemas on the Deep Web via Clustering Aggregation

9 years 5 months ago
Merging Interface Schemas on the Deep Web via Clustering Aggregation
We consider the problem of integrating a large number of interface schemas over the Deep Web, The scale of the problem and the diversity of the sources present serious challenges to the conventional manual or rule-based approaches to schema integration. To address these challenges, we propose a novel formulation of schema integration as an optimization problem, with the objective of maximally satisfying the constraints given by individual schemas. Since the optimization problem can be shown to be NP-complete, we develop a novel approximation algorithm LMax, which builds the unified schema via recursive applications of clustering aggregation. We further extend LMax to handle the irregularities frequently occurring among the interface schemas. Extensive evaluation on realworld data sets shows the effectiveness of our approach.
Wensheng Wu, AnHai Doan, Clement T. Yu
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where ICDM
Authors Wensheng Wu, AnHai Doan, Clement T. Yu
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