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- W3153549414 abstract "Constructing a binary tree, the Huffman algorithm introduced the method of text compression that helps to reduce the size keeping the original message of the file. Nowadays, Huffman-based algorithm assessment can be measured in two ways; one in terms of space, another is decoding speed. The requirement of memory for a text file is going to be reasonable while the time effectiveness of Huffman decoding is being more significant. Meanwhile, this research is introducing the adjacent distance array with Huffman principle as a new data structure for encoding, and decoding the Bengali text compression using transliterated English text. Since the transliterated English text accommodates to reduce the unit of symbols accordingly, we transliterated the Bengali text into English and then applied the Huffman principle with adjacent distance array. By calculating the ASCII values, adjacent distance array is used to save the distances for each adjacent symbols. Apart from the regular Huffman algorithm, a codeword has produced by traversing the whole Huffman tree for a character in case, respectively adopting the threshold value and adjacent distance array can skip the lengthy codeword and perform the decoding manner to decode estimating the distances for all adjacent symbols except traversing the whole tree. Our findings have acquired 27.54% and 20.94% compression ratios for some specimen transliterated Bengali texts, as well as accomplished a significant ratio on different corpora." @default.
- W3153549414 created "2021-04-26" @default.
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- W3153549414 date "2021-01-01" @default.
- W3153549414 modified "2023-10-03" @default.
- W3153549414 title "Introduction to Adjacent Distance Array with Huffman Principle: A New Encoding and Decoding Technique for Transliteration Based Bengali Text Compression" @default.
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- W3153549414 doi "https://doi.org/10.1007/978-981-33-4299-6_45" @default.
- W3153549414 hasPublicationYear "2021" @default.
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