A comparison of string distance metrics for name-matching tasks

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A comparison of string distance metrics for name-matching tasks (2003)

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by William W. Cohen , Pradeep Ravikumar , Stephen E. Fienberg

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448 - 11 self

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@INPROCEEDINGS{Cohen03acomparison,
    author = {William W. Cohen and Pradeep Ravikumar and Stephen E. Fienberg},
    title = {A comparison of string distance metrics for name-matching tasks},
    booktitle = {},
    year = {2003},
    pages = {73--78}
}

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Abstract

Using an open-source, Java toolkit of name-matching methods, we experimentally compare string distance metrics on the task of matching entity names. We investigate a number of different metrics proposed by different communities, including edit-distance metrics, fast heuristic string comparators, token-based distance metrics, and hybrid methods. Overall, the best-performing method is a hybrid scheme combining a TFIDF weighting scheme, which is widely used in information retrieval, with the Jaro-Winkler string-distance scheme, which was developed in the probabilistic record linkage community.

Keyphrases

distance metric name-matching task best-performing method different metric entity name java toolkit token-based distance metric probabilistic record linkage community hybrid scheme information retrieval hybrid method heuristic string comparators name-matching method tfidf weighting scheme jaro-winkler string-distance scheme different community edit-distance metric

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