Similarity flooding: a versatile graph matching algorithm and its application to schema matching
Stanford University · Leipzig University
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…
Citation impact
- FWCI
- 50.43
- Percentile
- 100%
- References
- 22
Authors
3Topics & keywords
- Computer science
- Matching (statistics)
- Schema matching
- Blossom algorithm
- Testbed
- USable
- Computation
- Algorithm
- Decent work and economic growth