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Adds subsumer matrix query and some similarity metrics #92

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Jun 15, 2019
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@hlapp hlapp commented Jun 14, 2019

The semantic similarity metrics included here are all solely based on graph structure. That is, by default they will use a subsumer matrix that has values 0 and 1, meaning each edge between a term and a subsumer is given equal weight. The metrics are Jaccard, Tanimoto (which is equal to Jaccard for W[i] in {0, 1}), and Cosine.

Tanimoto and Cosine could be used with weights other than {0, 1} as well, such as Information Content.

Addresses #37, perhaps in full.

The semantic similarity metrics included here are all solely based on
graph structure. That is, by default they will use a subsumer matrix
that has values 0 and 1, meaning each edge between a term and a
subsumer is given equal weight. The metrics are Jaccard, Tanimoto
(which is equal to Jaccard for W[i] in {0, 1}), and Cosine.

Tanimoto and Cosine could be used with weights other than {0, 1} as well,
such as Information Content.
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hlapp commented Jun 14, 2019

@uyedaj any feedback, based on documentation? Anything that seems missing?

@hlapp hlapp added the enhancement New feature or request label Jun 14, 2019
@hlapp hlapp merged commit d062182 into master Jun 15, 2019
@hlapp hlapp deleted the semsim branch June 15, 2019 21:32
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