Article,
Similarity Flooding: a versatile graph matching algorithm and its applications to schema matching
Data Engineering, 2002. Proceedings. 18th International Conference on, (2002)
Abstract
Matching elements of two data schemas or two data instances plays
a key role in data warehousing, e-business, or even biochemical applications.
In this paper we present a matching algorithm based on a fixpoint
computation that is usable across different scenarios. The algorithm
takes two graphs (schemas, catalogs, or other data structures) as
input, and produces as output a mapping between corresponding nodes
of the graphs. Depending on the matching goal, a subset of the mapping
is chosen using filters. After our algorithm runs, we expect a human
to check and if necessary adjust the results. As a matter of fact,
we evaluate the 'accuracy' of the algorithm by counting the number
of needed adjustments. We conducted a user study, in which our accuracy
metric was used to estimate the labor savings that the users could
obtain by utilizing our algorithm to obtain an initial matching.
Finally, we illustrate how our matching algorithm is deployed as
one of several high-level operators in an implemented testbed for
managing information models and mappings
