Arabic Short Text Compression

Omer,

doi:10.3844/jcssp.2010.24.28

Cited by 5 publications

(5 citation statements)

References 15 publications

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“…This paper aims to study two different methods of data compression techniques, and to compare their performance on Arabic and English text files. Also to exploit one of morphological features of the Arabic language, Citing way [5] (Omer and Khatatneh ,2010) to improve performance of Lempel Ziv Welch (LZW) techniques.…”

Section: Developing New Compression Techniques Based On the Morphologmentioning

confidence: 99%

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Efficiency Lossless Data Techniques for Arabic Text Compression

Jrai¹

2014

IJCSIT

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Study and evaluate the efficiency of LZW and BWT techniques for different categories of Arabic text files of different sizes. Compare these techniques on Arabic and English text files is introduced. Additional to exploiting morphological features of the Arabic language to improve performance of LZW techniques. We found that the enhanced LZW was the best one for all categories of the Arabic texts, then the LZW standard and BWT respectively.

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Section: Developing New Compression Techniques Based On the Morphologmentioning

confidence: 99%

“…Omer and Khatatneh [5] used the fact that Arabic letters have a single case to present a new technique which had been applied on Arabic short text. Huffman technique was used to measure the efficiency of the proposed technique.…”

Section: Related Workmentioning

confidence: 99%

Efficiency Lossless Data Techniques for Arabic Text Compression

Jrai¹

2014

IJCSIT

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“…Arabic is one of the most spoken Semitic languages ranking fifth in the world [28], [38], and Arabic Unicode UTF-8 scripts are used by 98.9% of all websites according to available usage statistics [39].…”

Section: Introductionmentioning

confidence: 99%

Improving LZW Compression of Unicode Arabic Text Using Multi-Level Encoding and a Variable-Length Phrase Code

Jrai,

Alsharari,

Almazaydeh

et al. 2023

IEEE Access

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This paper introduces a novel approach to enhance the efficiency of compressing Arabic Unicode text using the Lempel-Ziv-Welch (LZW) technique. This method includes two stages: transformation and compression. During the first phase, a multi-level scheme that works according to the level of words, syllables, and characters replaces multi-byte symbols with single-byte symbols, resulting in a binary output of 51%-75% smaller than the actual size and effective for compression. In the second phase: the outputs of the previous phase are received as inputs to the adaptive LZW technique, attached to a value representing the length of the initial phrase (minimum code length). This value is automatically determined according to the size of the data source to enhance the performance of LZW. The original data size is included in the compressed file to be used during the decompression process to detect the length of the initial phrase. The compression ratio achieved by the proposed method was compared to that of the traditional LZW technology that uses multi-byte encoded characters and a fixed initial length phrase, as well as two recent technologies, DEFLATE and Gzip. Experimental results indicate that our method achieves an average compression rate of about 71% and outperforms other methods for all forms of Arabic texts, with improved LZW able to compress an additional 7% or more or less of the files it compresses. Variable-length dictionary LZW continuously displays a significant difference in compression ratios for small files compared to modern methods, whether it uses a variable-width-encoding scheme only or with multi-level encoding as a precompression step. Multi-level schema can be used as a preprocess to other compression techniques, especially those that work efficiently with binary data. Also, the original data volume can be used as a private key within data security and encryption applications.INDEX TERMS Adaptive initial dictionary, Lempel-Ziv-Welch (LZW), multi-dictionaries, multi-level mapping, private key, unicode Arabic text, variable-length phrase code.

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“…Transferring data among mobile devices or computers can be time consuming. Moreover, storing such enormous amount of data can be prohibitively expensive (Omer and Khatatneh, 2010). For these reasons, there has been a demand to reduce the amount of data before saving or transferring it.…”

Section: Introductionmentioning

confidence: 99%

Dynamic with Dictionary Technique for Arabic Text Compression

Aburomman¹

2016

IJCA

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In this research paper we build a new, reliable, and sufficient algorithm for Arabic text language. The proposed algorithm should combine the features of the Huffman and Lempel Ziv algorithms, and is expected be able to reduce the general compression ratio. Our approach is different from Huffman algorithm in the sense that it assigns codes to n-gram symbols where n is a positive integer that is greater than or equal to one. Compared to Huffman algorithm, which assigns a code to each symbol individually, our approach is expected to assign codes to symbols in average. Our approach is different from Lempel Ziv algorithm in the sense that the size of dictionary that we build does not grow in an uncontrolled manner. The size of the dictionary is fixed and its size can be expected prior to process the text files that are to be compressed. This is because the size of each word in the dictionary we build is fixed and is equal to n. So for example, given that the number of different symbols in the text file at hand is m and that n is 2, the total number of entries in the dictionary that we propose to build will be m*m in the worst case.

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Arabic Short Text Compression

Cited by 5 publications

References 15 publications

Efficiency Lossless Data Techniques for Arabic Text Compression

Efficiency Lossless Data Techniques for Arabic Text Compression

Improving LZW Compression of Unicode Arabic Text Using Multi-Level Encoding and a Variable-Length Phrase Code

Dynamic with Dictionary Technique for Arabic Text Compression

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