PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Nottelmann H., Straccia U. A probabilistic approach to schema matching. In: Proceedings of the 27th European Conference on Information Retrieval (Santiago de Compostela, Spain, March 2005). Proceedings, vol. Lecture Notes in Computer Science 3408 pp. 81 - 95. (Lecture Notes in Computer Science). Springer Verlag, 2005.
 
 
Abstract
(English)
This paper introduces the first formal framework for learning mappings between heterogeneous schemas, which is based on probabilistic logics. This task, also called ``schema matching'', is a crucial step in integrating heterogeneous collections. As schemas may have different granularities, and as schema attributes do not always match precisely, a general-purpose schema mapping approach requires support for uncertain mappings, and mappings have to be learned automatically. The framework combines different classifiers for finding suitable mapping candidates (together with their weights), and selects that set of mapping rules which is the most likely one. Finally, the framework with different variants has been evaluated on two different data sets.
Subject Schema matching
H.3.5 Online Information Services. Data sharing


Icona documento 1) Download Document PDF


Icona documento Open access Icona documento Restricted Icona documento Private

 


Per ulteriori informazioni, contattare: Librarian http://puma.isti.cnr.it

Valid HTML 4.0 Transitional