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Paper Reference #19
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Hi there! The ESP paper is here: https://pubmed.ncbi.nlm.nih.gov/28284761/ |
great. any example script, how to use ESP for document vector representation? |
Morning all - we haven't used ESP to build document vector representations,
although it should be possible to do this if you can represent the document
as triples somehow. The closest we've come to this is this paper (
http://www.puttypeg.net/papers/expansion-by-analogy.pdf) in which we used
vector representations of concepts derived from triples to infer
connections between document and query vectors.
The semvecpy doesn't (yet) support training of models - all of this is done
with our Java package, Semantic Vectors (
https://github.com/semanticvectors/semanticvectors). The Wiki is a bit
sparse unfortunately, and I see we've yet to add documentation for ESP -
however the instructions to build a space are more or less the same as with
our previous model of triples, PSI:
https://github.com/semanticvectors/semanticvectors/wiki/PredicationBasedSemanticIndexing.
A good place to start might be to run through these and substitute
pitt.search.semanticvectors.ESP for pitt.search.semanticvectors.PSI.
Apologies for the lamentable state of the ESP documentation, and thanks for
the reminder to update the Wiki.
…On Thu, Aug 6, 2020 at 12:17 AM Pribadi HCR ***@***.***> wrote:
great. any example script, how to use ESP for document vector
representation?
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To add to that, if you’re curious about embedding predications (subject-relationship-object triples), there’s an example in this notebook: https://github.com/hannahburkhardt/predicting_ddis_with_esp/blob/master/predicting_ddis_with_esp.ipynb |
Hi,
What is the paper reference for this repo. Thanks
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