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13

WEBI
2005
Springer

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Measuring the Relative Performance of Schema Matchers

13 years 10 months ago

Measuring the Relative Performance of Schema Matchers

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Schema matching is a complex process focusing on matching between concepts describing the data in heterogeneous data sources. There is a shift from manual schema matching, done by human experts, to automatic matching, using various heuristics (schema matchers). In this work, we consider the problem of linearly combining the results of a set of schema matchers. We propose the use of machine learning algorithms to learn the optimal weight assignments, given a set of schema matchers. We also suggest the use of genetic algorithms to improve the process efficiency.

Shlomo Berkovsky, Yaniv Eytani, Avigdor Gal

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Internet Technology | Manual Schema | Schema Matchers | Schema Matching | WEBI 2005 |

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Added	28 Jun 2010
Updated	28 Jun 2010
Type	Conference
Year	2005
Where	WEBI
Authors	Shlomo Berkovsky, Yaniv Eytani, Avigdor Gal

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