Name
Abstract | ||
|---|---|---|
Gazetteers are catalogs of geographic features, typically classified using a feature type thesaurus. Integrating gazetteers is an issue that requires some strategy to deal with multiple thesauri, which represent different classifications for the geographic domain. This paper proposes an instance- based approach to define mapping rates between terms of distinct feature type thesauri in order to enable the reclassification of the data migrated from one gazetteer to another. A gazetteer is a database that stores information about a set of geographic features, classified using terms taken from a given feature type thesaurus. Gazetteers could be used as information sources of annotation systems of geographic data (Leme 2006). An annotation system could use many different gazetteers to get information about the data to be catalogued. However, as in a data-warehouse creation process, gazetteer integration requires aligning feature type thesauri, which is the central question we address in this paper. Our approach uses a mapping rate estimator that estimates weighted relationships between terms of distinct thesauri by pre-processing common instances from two gazetteers. Let G and G' using thesauri T and T', respectively, be the gazetteers to be integrated. Quite simply, if we have data about a geographic feature f from G classified as t (a term from T) and, again, data about f from G', but classified as t' (a term from T'), then f establishes some evidence that t' maps into t. Note that this strategy depends on the assumption that we can recognize when data from G and G' represent the same geographic feature or not. In this paper, we use the feature's spatial location from G and G', to deduce that a common set of data from G and G' indeed represent the same geographic features or not. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/978-3-540-73414-7_15 | GeoInfo |
Keywords | Field | DocType |
data migration,data warehouse | Data mining,Geographic information system,Information retrieval,Computer science,Database | Conference |
Citations | PageRank | References |
7 | 0.59 | 9 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniela F. Brauner | 1 | 43 | 5.31 |
| Marco A. Casanova | 2 | 1007 | 979.09 |
| Ruy Luiz Milidiú | 3 | 192 | 20.18 |