Sentence embeddings of the COVID-19 abstracts

Sentence embeddings of covid_abstracts' abstract texts, computed with the sbert package's pinned all-MiniLM-L6-v2 model (L2-normalized rows). Bundled so that text_hypergraph(construction = "knn") runs offline; rebuilt by data-raw/covid_embeddings.R.

Usage

covid_embeddings

Format

A numeric matrix with 165 rows (rownames = covid_abstracts$doc) and 384 columns.

Source

Computed from covid_abstracts with sbert::encode().

Examples

hg <- text_hypergraph(covid_abstracts, column = "abstract", id = "doc",
                      construction = "knn", k = 10,
                      embeddings = covid_embeddings)
hg
#> Text hypergraph: 165 documents (kNN embedding hyperedges: k = 10, cosine)
#> Hyperedges: 165 (kNN neighborhoods); sizes 11-11, median 11
#>                 doc               edge    weight
#>  2-s2.0-85085897904 2-s2.0-85085897904 1.0000000
#>  2-s2.0-85092100063 2-s2.0-85085897904 0.5784754
#>  2-s2.0-85092577169 2-s2.0-85085897904 0.5940401
#>  2-s2.0-85096991345 2-s2.0-85085897904 0.6156138
#>  2-s2.0-85096994563 2-s2.0-85085897904 0.5771233
#>  2-s2.0-85108879636 2-s2.0-85085897904 0.6228458
#>  2-s2.0-85109406490 2-s2.0-85085897904 0.5927937
#>  2-s2.0-85119298190 2-s2.0-85085897904 0.6315365
#>  2-s2.0-85124102536 2-s2.0-85085897904 0.5749891
#>  2-s2.0-85124535349 2-s2.0-85085897904 0.7546323
#> ... 1805 more rows