Percentage matching of text

[Bruce Eckel]

Thanks! The stringcmp.py module not only has nicely-documented
function calls, but also gives examples of how to use difflib.

It has also occurred to me that many of my examples will have text
that is "position consistent" between the control sample and test
sample -- that is, the stuff that matches will often be in exactly the
same place. So I might just be able to march through
position-by-position and do a simple comparison. (But I had to ask the
question on the newsgroup before I could think of the answer myself.
Funny how that works).

Anyway, I now seem to have some good footholds.

Friday, July 30, 2004, 9:20:06 AM, you wrote:

> On Fri, 2004-07-30 at 23:52, Bruce Eckel wrote:
>> What I'd like to do is find an algorithm that produces the results of
>> a text comparison as a percentage-match. Thus I would be able to
>> assert that my test samples must match the control sample by at least
>> (for example) 83% for the test to pass. Clearly, this wouldn't be a
>> perfect test but it would help flag problems, which is primarily what
>> I need.
>> 
>> Does anyone know of an algorithm or library that would do this? Thanks
>> in advance.

> Python implementations of a range of such algorithms can be found in
> Febrl - see section 9.2 of the manual:
> http://datamining.anu.edu.au/projects/linkage.html#prototype_software

> I suspect that a simple bigram comparison would meet your needs best. Or
> just use the Python difflib module in the standard Python library which
> implements the Ratcliff-Obershelp comparator.
> -- 

> Tim C

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Bruce Eckel    http://www.BruceEckel.com   mailto:BruceEckel at MailBlocks.com
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