PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Nottelmann H., Straccia U. Information retrieval and machine learning for probabilistic schema matching. In: ACM 14th Conference on Information and Knowledge Management (CIKM-05) (Bremen, Germany, November 2005). Proceedings, pp. 295 - 296. ACM, 2005.
 
 
Abstract
(English)
Schema matching is the problem of finding correspondences (mapping rules, e.g. logical formulae) between heterogeneous schemas. This paper presents a probabilistic framework, called sPLMap, for automatically learning schema mapping rules. Similar to LSD, different techniques, mostly from the IR field, are combined. Our approach, however, is also able to give a probabilistic interpretation of the prediction weights of the candidates, and to select the rule set with highest matching probability.
Subject information retrieval
H.3.3 Information Search and Retrieval


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