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where x i is a recommendation class from a recommendation set x.
In Table2 the recommendation class R c5 has the highest deviation value, so it is taken as a suspicious recommendation class and is added to the suspicious recommendation domain (SRdomain), and its SF is calculated.
where k = 1,2,3…,m − 1, and m is the distinct recommendation class value number in sorted R domain.
Since median is resistent to outlier, we have proposed a dissimilarity function that captures how dissimilar a recommendation class is from the median of the recommendation set.
Let R c k be the kth recommendation class of R domain and SRdomain be the set of suspicious recommendation classes from R domain, i.e., SRdomain ⊆ R domain.
After arranging the recommendations in their respective recommendation class R c i, we remove the recommendation classes with zero frequencies and calculate DF(R c i ) for each recommendation class using Equation 1. Table2 shows the sorted list of recommendation classes with respect to their dissimilarity value.
Similar(48)
Therefore, the recommendation classes {0.8,0.9} in SRdomain3 are considered as dishonest recommendation classes, and these recommendation classes are removed from the R domain.
Since the SF of SRdomain5 has the highest value, the recommendation classes {0.1,0.2,0.3} are considered as dishonest recommendation classes, and the recommendations that belong to these recommendation classes are considered as dishonest recommendations.
After detecting the set R domaindishonest, we remove all recommendations that fall under the dishonest recommendation classes.
The subset SRdomain k with the largest SF SRdomain k ) is considered as a set containing dishonest recommendation classes.
To help find the set of dishonest recommendation classes from the set of recommendations in R domain, Arning et al.[27] defined a measure called smoothing factor (SF).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com