Semantic network extraction from text corpora
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License: MIT License
Semantic network extraction from text corpora
License: MIT License
Begin the related works section of this paper. That should include a BibTex or equivalent file from which the references section of the LaTeX paper is drawn.
Provide and document an information theoretic way of detecting stopwords from the corpus statistics.
C.f. http://terrierteam.dcs.gla.ac.uk/publications/rtlo_DIRpaper.pdf
Begin the LaTeX paper for this project
Examine the word2vec project and see if that work can be replicated.
Compare this with nframe.
I'm talking in the staff meeting about what counts as good value for D-Lab. Can you make a simple D-Lab branded github page for this project? I think it'd be good for you too.
Allow for nframing with a variable number of dimensions (e.g. using n-tuples of cooccurences in subsets). Show difference in performance and explain why.
Add the first pass of a semantic network extraction algorithm. Include a notebook to illustrate its functionality.
Identify a task that could use nframe. Attempt that task using a topic modeling framework. Compare the performance of the two systems.
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