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Exact(14)
From these records we identified the Network Ecology publications using the topic terms network, graph theory, and web, while controlling for the usage of misleading phrases.
Fig. 9 Mapper and reducer for semantic terms generation from cluster topic terms.
The Mapper computes the semantic similar terms for each topic term generated by the document cluster and reducer aggregate these terms and counts the frequencies of these terms (topic terms and semantic similar terms of topic terms) aggregately.
The mapper and reducer for semantic terms generation from cluster topic terms is presented in the Fig. 9.
The mapper and reducer for topic terms generation from document clusters is shown in the Fig. 8.
Then the terms are arranged in the descending order of frequency and top N topic terms (including the semantic similar terms) are selected.
Similar(46)
When duplicate or confusing topics arose, curators were told to "inject" a more accurate Topic term.
where is the term vector of the user, and is the topic term vector.
In the third stage, semantic similar terms are computed for each topic term generated in previous stage.
With Topic Insights, media partners just enter a topic term, and Facebook returns data about anyone who mentioned a world related to that term.
We then calculate the cosine similarity between the profile term vector and the topic term vector to get the member's inner profile rank.
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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