Abstract
This article represents the method of the text’s parameters identification and their classification with the help of archiving. Using the direct bond between the archiving with LZ77 and Huffman algorithm and entropy, the text’s characteristics are identified, and they help to define its language, style, authorship, and cluster data files by their topic relevance
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