Please use this identifier to cite or link to this item:
|Title:||Validating multi-column schema matchings by type|
|Source:||Dai, B.T., Koudas, N., Srivastava, D., Tung, A.K.H., Venkatasubramanian, S. (2008). Validating multi-column schema matchings by type. Proceedings - International Conference on Data Engineering : 120-129. ScholarBank@NUS Repository. https://doi.org/10.1109/ICDE.2008.4497420|
|Abstract:||Validation of multi-column schema matchings is essential for successful database integration. This task is especially difficult when the databases to be integrated contain little overlapping data, as is often the case in practice (e.g., customer bases of different companies). Based on the intuition that values present in different columns related by a schema matching will have similar "semantic type", and that this can be captured using distributions over values ("statistical types"), we develop a method for validating 1-1 and compositional schema matchings. Our technique is based on three key technical ideas. First, we propose a generic measure for comparing two columns matched by a schema matching, based on a notion of information-theoretic discrepancy that generalizes the standard geometric discrepancy; this provides the basis for 1:1 matching. Second, we present an algorithm for "splitting" the string values in a column to identify substrings that are likely to match with the values in another column; this enables (multi-column) 1:m schema matching. Third, our technique provides an invalidation certificate if it fails to validate a schema matching. We complement our conceptual and algorithmic contributions with an experimental study that demonstrates the effectiveness and efficiency of our technique on a variety of database schemas and data sets. © 2008 IEEE.|
|Source Title:||Proceedings - International Conference on Data Engineering|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 14, 2017
WEB OF SCIENCETM
checked on Nov 19, 2017
checked on Dec 10, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.