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I've been working for a few years on an English-language thesaurus project, which combines a few sources (e.g. WordNet, Wiktionary Thesaurus, Moby Thesaurus, Word2vec) to make a large thesaurus. Currently I have the data defined as a list of lists. And each link has a score (higher = stronger), so "hotel" and "inn" might have a score of 2.0; but "hotel" and "fleabag" has a score of 0.2. High scores are near synonyms, low scores are more distant associations. I've been able to use Dijkstra and A* to find links between words (so-called "synonym chains").

Is there a type of graph database and/or analysis tools which is ideally suited for this sort of data? Word relationship strengths are often asymmetric. For example "Hoover Dam" links to "Herbert Hoover" more strongly than "Herbert Hoover" links back to "Hoover Dam". I'm interested in better ways to find the links between words, find unrelated words, measure word similarity.

I'd appreciate any new pointers/direction.

Michael Douma
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Interesting question. Not sure about the best data structure, but for processing, you can look at shell neighbors within this package: https://grispy.readthedocs.io/en/latest/api.html

Daniel Zrust
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