Sentence examples for relevance scoring from inspiring English sources

Using a relevance scoring algorithm based on alignment qualities (see Methods for details), the most relevant description was selected as representative for the query sequence.

After applying thesaurus and relevance scoring to the 2,311 keywords, 352 keywords from the 1990 1999 period remained and 1,033 keywords from the 2000 2014 period.

Our approach exploits domain ontology to consider relationships among terms in the relevance scoring process.

For this comparison, we used a stricter keyword occurrence cutoff of 25 or more and also applied relevance scoring to obtain higher specificity in the time analysis.

Within the clinical literature, other forms of relevance scoring are based on discrete or discontinuous algorithms which calculate an estimate for individuals only using those items for which they have reach a certain threshold.

The benefits of RWR for node relevance scoring have been discussed extensively in the literature (Tong et al., 2008) and are already used in current approaches for disease-gene prioritization (Köhler et al., 2008).

Figure 3 demonstrates the relationship between "Relevance score" and the number of relation related GSE.

It can be seen that the "Relevance score" increases with the increases of related GSE numbers.

(T times W) relevancies were calculated (i.e., each word had one relevance score per topic) and used to sort the most relevant words per topic.

As the one asking for results, users have to decide things like whether to exclude words with relevance scores at certain thresholds or maybe to only match words in a whitelist they have provided.

Pathologies with Relevance Score > 1.0 are listed.