The maintenance and updating of Statistics Austria's business register
requires a regularly matching of the register against other data sources;
one of them is the register of tax units of the Austrian Federal Ministry of
Finance. The matching process is based on string comparison via bigrams of
enterprise names and addresses, and a quality class approach assigning pairs
of register units into classes of different compliance (i.e., matching quality)
based on bigram similarity values and the comparison of other matching variables,
like the NACE code or the year of foundation.
Based on methodological research concerning matching techniques carried
out in the DIECOFIS project, an empirical comparison of the bigram method
and other string matching techniques was conducted: the edit distance, the
Jaro algorithm and the Jaro-Winkler algorithm, the longest common subsequence
and the maximal match were selected as appropriate alternatives and
evaluated in the study.
This paper briefly introduces Statistics Austria's business register and the corresponding
maintenance process and reports on the results of the empirical
study.
| Identifer | oai:union.ndltd.org:VIENNA/oai:epub.wu-wien.ac.at:5630 |
| Date | January 2005 |
| Creators | Denk, Michaela, Hackl, Peter, Rainer, Norbert |
| Publisher | Austrian Statistical Society, c/o Bundesanstalt Statistik Austria |
| Source Sets | Wirtschaftsuniversität Wien |
| Language | English |
| Detected Language | English |
| Type | Article, PeerReviewed |
| Format | application/pdf |
| Rights | Creative Commons: Attribution 4.0 International (CC BY 4.0) |
| Relation | http://www.ajs.or.at/index.php/ajs/article/view/vol34%2C%20no3%20-%201, http://www.ajs.or.at/index.php/ajs, http://www.ajs.or.at/index.php/ajs/about/editorialPolicies#openAccessPolicy, http://eeyore.wu-wien.ac.at/stat4/hackl/home.html, http://epub.wu.ac.at/5630/ |
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