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Frequency-aware Similarity Measures Why Arnold Schwarzenegger is Always a Duplicate Dustin Large Felix Baumann Basso Platter Institute, Potsdam, Germany first name. Last name hip.uni-potsdam.DE ABSTRACT
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Frequency-aware similarity measures are techniques that are used to quantify the similarity between two sets of data by taking into account the frequency distribution of the elements within each set.
The individuals or organizations that are responsible for managing and analyzing data sets are required to file frequency-aware similarity measures in order to assess the similarity between different data sets.
To fill out frequency-aware similarity measures, you need to calculate the frequency distribution of elements within each set of data and then apply the appropriate similarity measure technique to compare the distributions.
The purpose of frequency-aware similarity measures is to provide a quantitative assessment of the similarity between two sets of data, taking into account the frequency distribution of the elements within each set.
On frequency-aware similarity measures, you need to report the specific similarity measure technique used, the frequency distribution of elements within each set of data, and the result or score indicating the similarity between the two sets.
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