names-matcher 1.1.1

Fuzzy biject people's names between two lists.

names-matcher

Fuzzy biject people's names between two lists.

Let's define an identity as a series of names belonging to the same person. The algorithm is:

1. Parse, normalize, and split names in each identity. The result is a set of strings for each identity.
2. Define the similarity between identities as the Jaccard similarity between their sets of strings.
3. Construct the distance matrix between identities in two specified lists.
4. Solve the Linear Assignment Problem (LAP) on that matrix.

We use metaphones in the normalization step to reduce the influence of different spelling and typos. We use lapjv to solve the LAP, so our solution scales to ~1000-s of identities. If you have a bigger problem size, you should use MinHashes (e.g. http://ekzhu.com/datasketch/) over the identity sets produced by reap_identity(). Feel free to PR them.

Example:

>>> from names_matcher import NamesMatcher
>>> NamesMatcher()([["Vadim Markovtsev", "vmarkovtsev"], ["Long, Waren", "warenlg"]], \
                    [["Warren"], ["VMarkovtsev"], ["Eiso Kant"]])
(array([1, 0], dtype=int32), array([0.75      , 0.57142857]))

The first resulting tuple element is the mapping indexes: of same length as the first sequence, with indexes in the second sequence. The second element is the corresponding confidence values from 0 to 1.

Installation

pip3 install names-matcher

Command line interface

Given one identity per line in two files, print the matches to standard output:

python3 -m names_matcher path/to/file/1 path/to/file/2

Each identity is several names merged with |, for example:

Vadim Markovtsev|vmarkovtsev|vadim

Contributing

Contributions are very welcome and desired! Please follow the code of conduct and read the contribution guidelines.

License

Apache-2.0, see LICENSE.