Common Features of Well-known Empirical Laws in Scientometrics: Data Grouping Based on Frequency Distribution

To study four well-known empirical laws in Bibliometrics and Scientometrics (Lutka, Bradford, Zipf and Pareto) and group their data based on frequency distribution.
It is an applied and descriptive research which analyzes documents. Data is categorized based on frequency distribution through studying data related to four scientometrics laws.
Data in four groups contain the object rank, the studied feature and the frequency of the feature in that object. In each law, data are classified into different groups: Pareto (2 groups), Bradford (3 groups), Lutka (equal to the maximum frequency), and Zipf (equal to text words).
Grouping of objects and the number of objects inside each group follow a certain distribution. These empirical laws can be used to group different objects based on plenty of features.