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Recently, text mining techniques have been rapidly developed for automatically extracting key information from massive text data.
In my own text collection, the figure is about 10%.
We believe that this collection is the largest Persian text collection, so far.
After completing the massive text, he composed the operas in the order of the story.
Our work aimed to extract more polarity shifting patterns from massive text corpora.
Summarization of text collection involves intensive text processing and computations to generate the summary.
Summarizing large text collection is an interesting and challenging problem in text analytics.
Effective analysis of large text collections remains a challenging problem given the growing volume of available text data.
In text summarization a large collections of text documents are transformed to a reduced and compact text document, which represents the digest of the original text collections.
Clustering provides better summarization units (text segments) for summarizing the text collections.
The topic model – a recently-developed Bayesian model for text document collections [38] – is considered a state-of-the-art algorithm for extracting semantic structure from text collections.
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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