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Reply to: fuzzy matching

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Previously on "fuzzy matching"

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  • Olly
    replied
    right then...I'm getting there with this
    I've built a small table from existing matched data of names and abbreviations
    eg. William = Bill

    I'd really like a full multicultural data set...any pointers please?

    Leave a comment:


  • mudskipper
    replied
    Originally posted by Olly View Post
    oops forgot to add....this is running under MS Access
    Maybe this will be useful...

    Leave a comment:


  • Platypus
    replied
    I've looked into this very heavily in the past.

    Arguably, SMITH and MSITH are the same name, due to a typo. Or SMITH and WMITH

    In my case, I used several algorithms to judge similarity between names and addresses, and weighted them to give a final score.

    Here's a link you may find useful:
    Approximate string matching - Wikipedia, the free encyclopedia

    Also Google for N-Gram, Levenstein and Hamming.

    Leave a comment:


  • Olly
    replied
    This looks like the puppy Fuzzy Matching Demo in Access - CodeGuru

    a DB of names and uses a few fuzzy algorithms...looks like I've got my work cut out digging through it all

    Leave a comment:


  • Olly
    replied
    oops forgot to add....this is running under MS Access

    Leave a comment:


  • rsingh
    replied
    There's also a version in MSSQL for this.

    See the following page

    Leave a comment:


  • doodab
    replied
    Originally posted by Olly View Post
    Hi,
    I've got list of people's names that I need to match against another list of peeps

    Anyone know of any good routines for this kind of fuzzy matching?
    Maybe you know of a table of common mistakes. Mac = Mc etc Mike = Michael ?

    thanks very much
    I've used oracle's implementation of this before.

    Soundex - Wikipedia, the free encyclopedia

    Leave a comment:


  • Olly
    started a topic fuzzy matching

    fuzzy matching

    Hi,
    I've got list of people's names that I need to match against another list of peeps

    Anyone know of any good routines for this kind of fuzzy matching?
    Maybe you know of a table of common mistakes. Mac = Mc etc Mike = Michael ?

    thanks very much

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