jaccard

Calculate jaccard similarity metric for two sets a and b

Analysis and visualization of similarities between epilepsy ontologies based on text mining results by comparing ranked lists of co-occurring drug terms in the BioASQ corpus. The ranked result lists of neurological drug terms co-occurring with terms from the epilepsy ontologies EpSO, ESSO, EPILONT, EPISEM and FENICS undergo further analysis. The source data to create the ranked lists of drug names is produced using the text mining workflows described in Mueller, Bernd and Hagelstein, Alexandra (2016) <doi:10.4126/FRL01-006408558>, Mueller, Bernd et al. (2017) <doi:10.1007/978-3-319-58694-6_22>, Mueller, Bernd and Rebholz-Schuhmann, Dietrich (2020) <doi:10.1007/978-3-030-43887-6_52>, and Mueller, Bernd et al. (2022) <doi:10.1186/s13326-021-00258-w>.

Bernd Mueller

epos

Epilepsy Ontologies' Similarities

jaccard function

<dl><dt>ainterb</dt>
<dd>integer value with number of intersecting elements between set a and b</dd>
<dt>aunionb</dt>
<dd>integer value with number of union elements between set a and b</dd>
<dt>lengtha</dt>
<dd>length of set a</dd>
<dt>lengthb</dt>
<dd>length of set b</dd></dl>

Arguments

Calculate jaccard similarity metric for two sets a and b — jaccard

<dl>

<dt>ainterb</dt>
<dd>integer value with number of intersecting elements between set a and b</dd>


<dt>aunionb</dt>
<dd>integer value with number of union elements between set a and b</dd>


<dt>lengtha</dt>
<dd>length of set a</dd>


<dt>lengthb</dt>
<dd>length of set b</dd>

</dl>

jaccard: Calculate jaccard similarity metric for two sets a and b

Description

Usage

Value

Arguments

Examples