Open AccessFrequency Distribution Fitting for Electronic Documents
Author(s) -
Arockia David Roy Kulandai
Publication year - 2021
Publication title -
international journal of applied sciences and smart technologies
Language(s) - English
Resource type - Journals
eISSN - 2685-9432
pISSN - 2655-8564
DOI - 10.24071/ijasst.v3i1.2854
Subject(s) - frequency distribution , byte , computer science , natural language , distribution (mathematics) , natural language processing , natural (archaeology) , information retrieval , artificial intelligence , statistics , mathematics , geography , programming language , mathematical analysis , archaeology
Studies of frequency distributions of natural language elements have identified some distributions that offer a good fit. Using electronic documents, we show that some of these distributions cannot be used to model the frequency of bytes in electronic documents even if these documents represent natural language documents.