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maurever avatar maurever commented on June 18, 2024

Hi @dmresearch15. Thanks for reporting this issue.

It looks like there is a bug, that we cannot return results without an error for an unseen word.

We definitely need to fix it.

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maurever avatar maurever commented on June 18, 2024

I reproduced the error by this code:

job_titles <- h2o.importFile("https://s3.amazonaws.com/h2o-public-test-data/smalldata/craigslistJobTitles.csv",  col.names = c("category", "jobtitle"), col.types = c("String", "String"), header = TRUE)

words <- h2o.tokenize(job_titles, " ")
vec <- h2o.word2vec(training_frame = words)

// pass    
syn <- h2o.findSynonyms(vec, "teacher", count = 20)
print(syn)

// fail    
syn2 <- h2o.findSynonyms(vec, "Tteacher", count = 20)
print(syn2)

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dmresearch15 avatar dmresearch15 commented on June 18, 2024

I'm presently incorporating this into my project. It's helpful to have a timeframe for resolving this issue.

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maurever avatar maurever commented on June 18, 2024

Hi @dmresearch15, I fixed the bug in R API here: #16280. Hopefully, this change will be released in the fix release at the end of the week.

If the model can't find synonyms, it failed with the error you shared. The question still is, why can your model find synonyms for "national" and not for "National"? You may need to tune your model a little bit.

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