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Please use this identifier to cite or link to this item: http://lrcdrs.bennett.edu.in:80/handle/123456789/4485
Title: Zip Craft: Innovating File Compression with Huffman and Lempel Algorithms
Authors: Jain, Vikas Kumar
Singh, Anushka
Sharma, Ansh
Aakash
Issue Date: 2023
Publisher: Rawat Prakashan
Abstract: Pioneers of file compression, the Zip It project makes use of a clever combination of cutting-edge technologies, most notably the Huffman encoding and the Lempel algorithm. This novel method tackles important facets of data security while simultaneously guaranteeing good compression ratios. Particularly, Zip It is proud of its dedication to user accessibility, with a Python-based graphical user interface (GUI) that accommodates users with different degrees of technical proficiency. Novel Compression Methods: Lempel Compression technique: The Lempel compression technique is the foundation of Zi pit's inventiveness. By methodically reducing file sizes while maintaining data integrity, this calculated decision guarantees a dependable and effective decompression procedure. The way the Lempel compression technique works is by finding character sequences that appear repeatedly in the material, Redundancy is greatly decreased by substituting a reference for a sequence after it has been discovered. When there is recurrence or resemblance in some parts of the data, this technique works especially well. The methodical identification and compression of these patterns by the Lempel algorithm guarantees the minimization of file sizes without sacrificing the original data. Additionally, the Lempel algorithm's strategic decision enhances the decompression process' dependability and effectiveness. The approach ensures that the information is correctly recovered during decompression by cleverly reconstructing the original data from the compressed form. This dependability highlights the algorithm's function in preserving data integrity throughout the compression and decompression lifespan, which is important for users that depend on the decompressed data for a variety of applications.
URI: http://lrcdrs.bennett.edu.in:80/handle/123456789/4485
ISSN: 978-93-82206-02-6
Appears in Collections:Book Chapters_ SCSET

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