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For constructing a word language model we used the lyrics text of 4470 songs, containing over 1.2 million word instances, retrieved from http://www.azlyrics.com/.com/
For each word i used by each community j we calculated its relative word usage frequency f j ( i ), i.e., the proportion of the total word instances that were word i.
The database comprises 221 writers contributing a total of more than 1700 forms with 13,049 labeled text lines and 86,272 word instances from a dictionary of 11,059 words.
In our model, D documents are generated drawing word instances repeatedly with replacement from a vocabulary of V words.
This suggested that we could not rely on only the word instances themselves as features.
In the current version of MOST/MOST+, word instances were extended by substituting bases one by one.
Similar(48)
Word (WRD): the final feature used was the word instance itself.
To deduce context and be able to use supervised machine learning methods to predict click-words, we represented each word instance by a set of features, determined by both our own studies and prior observations in the literature.
The value of this feature is 'is-an-abbreviation' if the word instance in our dataset is matched exactly to a term from that abbreviation list or 'is-not-an-abbreviation' otherwise.
Computational results have been carried out on large real-word instances.
[Snapshot]/summary.txt Human readable summary of the topic model, with top-20 terms per topic and how many words instances of each have occurred.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com