Comments (3)
Why? What's your use case? And how do you define "most probable"?
from python-wordsegment.
Your algorithm is probabilistic, or at least it uses some sort of score. If I'm using wordsegment as part of a language modelling pipeline, I may want to propagate that measure of uncertainty.
I'm using it to model language in passwords. After a password is segmented, part-of-speech and semantic tags are inferred. The model sees these features and updates its beliefs. The devil is in ambiguity: therapistfinder
has two meanings depending on segmentation. Ideally, the model should account for both.
from python-wordsegment.
Ok, pull request welcome.
from python-wordsegment.
Related Issues (20)
- Buffering issue in main() HOT 5
- ZeroDivisionError HOT 2
- License question HOT 7
- max() arg is an empty sequence HOT 1
- How to add custom values? HOT 1
- unigrams HOT 1
- import error HOT 2
- Text with numbers doesn't segment as expected HOT 3
- `exhilarate` does not segment as expected HOT 1
- Can I use this from C or C++? HOT 1
- Please allow separation of numbers from text HOT 1
- Corpus python HOT 1
- russian language HOT 2
- Training on new, modern data. HOT 1
- feature_request(mode): preserve all punctuation marks HOT 2
- Support for Other Languages HOT 2
- RecursionError on segment call HOT 6
- 'helloworld' does not segment as expected HOT 3
- Words segmenting in one direction, but not another. HOT 1
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from python-wordsegment.