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anhaidgroup / py_stringmatching

A comprehensive and scalable set of string tokenizers and similarity measures in Python
https://sites.google.com/site/anhaidgroup/projects/py_stringmatching
BSD 3-Clause "New" or "Revised" License
135 stars 16 forks source link

Fix Monge-Elkan example #63

Closed wynksaiddestroy closed 2 years ago

wynksaiddestroy commented 4 years ago

The Monge-Elkan similarity of "Comput. Sci. and Eng. Dept., University of California, San Diego" and "Department of Computer Science, Univ. Calif., San Diego" is wrong in the example. The correct value is 0.8364448130130768.

Python 3.7.7 (default, Mar 10 2020, 15:43:33) 
[Clang 11.0.0 (clang-1100.0.33.17)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import py_stringmatching as sm
>>> me = sm.MongeElkan()
>>> me.get_raw_score(['Comput.', 'Sci.', 'and', 'Eng.', 'Dept.,', 'University', 'of', 'California,', 'San', 'Diego'], ['Department', 'of', 'Computer', 'Science,', 'Univ.', 'Calif.,', 'San', 'Diego'])
0.8364448130130768
coveralls commented 4 years ago

Coverage Status

Coverage remained the same at 99.903% when pulling 23e1cd0495dbeacd71e759978b2e6f08f5c01b16 on wynksaiddestroy:fix-monge-elkan-example into 45c3a09c27e44691f0e850fe060640fa2adc3ce7 on anhaidgroup:master.

wynksaiddestroy commented 2 years ago

Thanks :heart: