Sentence examples for relevance for each from inspiring English sources

The respondent was asked to rate the perceived relevance for each domain using a 5-point scale (0 = not relevant, 1 = slightly relevant, 2 = relevant, 3 = very relevant, 4 = extremely relevant).

Not every topic is of relevance for each region.

An analysis of relevance for each feature acquired in these two scenarios is presented.

BP-MLL is also quite good in the ranking measures (apart from one-error) and in the micro and macro averaged AUC measures, which indicates that it also computes good estimates of the probability of relevance for each label.

As previously defined, the privacy relevance for each attribute of the reference context set a is 0. Hence the overall privacy relevance is d ( a, b ) = ( 1 − 0 ) + ( 0 − 0 ) + ( 0 − 0 ) 2 + 1 + 2 = 1 5 = 0.2.

The color-scaled visual support both in the timeline and the information browser of VisArchive, allows the PM to identify these relevance-ranked files and to identify the level of relevance for each file in the information browser.

With relevance feedback a first iteration of documents retrieved by a retrieval system is evaluated for relevance, e.g., the searcher makes relevance judgments for each retrieved document.

To assess the content validity of the 40 items, a subgroup of patients (N = 26) were asked to rate the relevance or importance of each item on a scale from one to three: 1 = irrelevant, unimportant 2 = somewhat relevant, somewhat important 3 = very relevant, very important Mean relevance scores for each item were calculated.

The relevance scores for each semantic were used to calculate an overall relevance score in regard to a set Q of semantics selected by a user (see explanation in Appendix 1).

Bakhtin's notion of the carnivalesque, with its potential to upset the hierarchies of power and turn the world upside down, had a particular relevance for Brazil, where each year the keys of cities, such as Rio de Janeiro, are handed to Rei Momo (the king of carnival) for three days of riotous living.

We used documents annotated with the relevance labels as input to the machine-learning methods, and we trained the SVM classifier to predict the relevance label for each document and used these predictions for ranking.