A Method for Estimating the Precision of Placename Matching

Information in digital libraries and information systems frequently refers to locations or objects in geographic space. Digital gazetteers are commonly employed to match the referred placenames with actual locations in information integration and data cleaning procedures. This process may fail due t...

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Bibliographic Details
Published in:IEEE transactions on knowledge and data engineering 2007-08, Vol.19 (8), p.1089-1101
Main Authors: Doerr, M., Papagelis, M.
Format: Article
Language:English
Subjects:
Applied sciences
Cleaning
Computer science
control theory
systems
Control systems
Data engineering
Data mapping
Data processing. List processing. Character string processing
data translation
database integration
Deviation
Digital libraries
Estimating
Exact sciences and technology
Failure analysis
Hierarchies
Information systems
Information systems. Data bases
knowledge and data engineering tools and techniques
Mapping
Mathematical models
Memory organisation. Data processing
Recall
Software
Software libraries
Statistical analysis
Stochastic processes
Studies
Terminology
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Summary:Information in digital libraries and information systems frequently refers to locations or objects in geographic space. Digital gazetteers are commonly employed to match the referred placenames with actual locations in information integration and data cleaning procedures. This process may fail due to missing information in the gazetteer, multiple matches, or false positive matches. We have analyzed the cases of success and reasons for failure of the mapping process to a gazetteer. Based on these, we present a statistical model that permits estimating 1) the completeness of a gazetteer with respect to the specific target area and application, 2) the expected precision and recall of one-to-one mappings of source placenames to the gazetteer, 3) the semantic inconsistency that remains in one-to-one mappings, and 4) the degree to which the precision and recall are improved under knowledge of the identity of higher levels in a hierarchy of places. The presented model is based on statistical analysis of the mapping process of a large set of placenames itself and does not require any other background data. The statistical model assumes that a gazetteer is populated by a stochastic process. The paper discusses how future work could take deviations from this assumption into account. The method has been applied to a real case.
ISSN:1041-4347
1558-2191
DOI:10.1109/TKDE.2007.1033