keymanapp
feat(web): provide lexicon probabilities directly on the search path 📚
This PR was originally part of #10973.
In order to efficiently traverse a full lexical efficiently for dictionary-based wordbreaking, it's best to directly provide relevant probability data as efficiently as possible. Fortunately, it's easily possible to make this O(1) on the lexical model's internal iterator - the LexiconTraversal type. It would take O(log(N)) time to recompute it via the model's .predict method instead.
Note that this provides two different probability value types:
- The probability of each reached entry.
- The probability of the highest-frequency entry either represented by the current node or by any of its descendants.
There are uses for this outside of dictionary-based wordbreaking, too. The latter 'probability' listed above can be useful for optimizing the correction-search - if a path only produces low-frequency words, we should consider other paths that could yield higher-frequency words first.
There's also notable potential for being able to merge / blend two different models together via their LexiconTraversal iterators in this manner. Noting our upcoming push toward #11872, this would facilitate a fantastic way to achieve that goal - to create a stand-in model for the OS's dictionary and blend that with the loaded lexical-model via traversals.
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