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Identifies occurrences of term duplications.
Fig. 6 Number of glossary-internal occurrences of term duplication.
Each glossary has been analyzed individually to identify glossary-internal occurrences of term duplication.
where (textit {tf}_{t}^{;(c)}) express the absolute frequency, i.e., the number of occurrences, of term t in corpus c.
The number of identified occurrences of term duplication for each glossary is listed in Fig. 6, thus representing an excerpt of the whole glossaries.
Term frequency is calculated as tfi,j = ni,j/∑nk,j, for each term i and document j where nk,j is the number of occurrences of term k in document j.
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Next, the reduce function (Algorithm 2) receives the shuffled key-value pairs and iterates values (terms) per key (hashtag) summing the occurrences of terms for each key.
The weight calculated for an aspect has been described based on frequency of occurrences of terms associated with this aspect interpreted as importance measure as has been described in [12, 18, 72].
Such intuitive assumption may be useful for many practical cases, but it is a known fact that the number of occurrences of terms in a corpus decreases exponentially [36].
Signification contrasts with the other properties of terms in one major respect, for the other properties (perhaps with the exception of appellation in some authors, and natural supposition) are all properties of terms relative to their occurrence in particular propositions — indeed, they are properties of occurrences of terms.
We similarly search for embedded occurrences of terms from the Chemical Entities of Biological Interest (ChEBI) ontology (Degtyarenko, 2003) and substitute them with a distinct generic label.
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error of term
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CEO of Professional Science Editing for Scientists @ prosciediting.com