Relevant bibliographies by topics / Huffman algorithm

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Academic literature on the topic 'Huffman algorithm'

Author: Grafiati
Published: 3 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Huffman algorithm"

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Okazaki, Hiroyuki, Yuichi Futa, and Yasunari Shidama. "Constructing Binary Huffman Tree." Formalized Mathematics 21, no. 2 (2013): 133–43. http://dx.doi.org/10.2478/forma-2013-0015.

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Summary Huffman coding is one of a most famous entropy encoding methods for lossless data compression [16]. JPEG and ZIP formats employ variants of Huffman encoding as lossless compression algorithms. Huffman coding is a bijective map from source letters into leaves of the Huffman tree constructed by the algorithm. In this article we formalize an algorithm constructing a binary code tree, Huffman tree.
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Hasan, Syahril, Saiful Do Abdullah, and Arisandy Ambarita. "Penerapan Algoritma Huffman Coding Dalam Menghemat Ruang Penyimpanan Data Multimedia File (Teks dan Gambar) Berbasis Python." Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika 7, no. 2 (2024): 118–27. http://dx.doi.org/10.47324/ilkominfo.v7i2.268.

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Abstrak: Kompresi adalah teknik yang digunakan untuk mengompres data agar sesuai dengan ukuran pada media yang digunakan. seperti backup data, transmisi data, dan keamanan data. Algoritma Huffman dalam kompresi teks dapat menghasilkan pengurangan ukuran file yang signifikan tanpa kehilangan informasi, struktur pohon Huffman dan pengkodean karakter memberikan wawasan yang mendalam tentang cara algoritma bekerja. Metode Pengembangan yang gunakan adalah Algoritma Huffman yang di mulai dengan Pengumpulan Frekuensi, Pembuatan Tree Huffman, Pembuatan Kode Huffman, Pembuatan Tabel Kompresi, dan Kompr
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Priyono, Eko, and Hindayati Mustafidah. "Text Compression Using the Shannon-Fano, Huffman, and Half–Byte Algorithms." International Journal of Scientific Research and Management (IJSRM) 12, no. 09 (2024): 1422–27. http://dx.doi.org/10.18535/ijsrm/v12i09.ec01.

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Background and Objectives: File sizes increase as technology advances. Large files require more storage memory and longer transfer times. Data compression is changing an input or original data into another data stream as output or compressed data which is smaller in size. Existing compression techniques include the Huffman, Shannon-Fano, and Half-Byte algorithms. Like algorithms in computer science, these three algorithms offer advantages and disadvantages. Therefore, testing is needed to determine which algorithm is most effective for data compression, especially text data. Methods: Applying
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Gupta, Apratim. "Huffman Algorithm Improvement." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 6 (2017): 903–4. http://dx.doi.org/10.23956/ijarcsse/v7i6/0341.

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Kairišs, Edgars, and Mihails Kijaško. "HUFFMAN COMPRESSION ALGORITHM." HUMAN. ENVIRONMENT. TECHNOLOGIES. Proceedings of the Students International Scientific and Practical Conference, no. 21 (April 19, 2017): 131–34. http://dx.doi.org/10.17770/het2017.21.3594.

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In modern IT world, we are returning to the problem of low storage space. May be typically users do not see this problem and still there is more data that companies collect and should store. In this work author analyzed Huffman compression algorithm it’s effectiveness, working principles and examples of usage.
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Singh, Satpreet, and Harmandeep Singh. "Improved Adaptive Huffman Compression Algorithm." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 1, no. 1 (2011): 16–22. http://dx.doi.org/10.24297/ijct.v1i1.2602.

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In information age, sending the data from one end to another endneed lot of space as well as time. Data compression is atechnique to compress the information source (e.g. a data file, aspeech signal, an image, or a video signal) in possible fewnumbers of bits. One of the major factors that influence the DataCompression technique is the procedure to encode the sourcedata and space required for encoded data. There are many datacompressions methods which are used for data compression andout of which Huffman is mostly used for same. Huffmanalgorithms have two ranges static as well as adaptive. Sta
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Zhan, Honghui. "Image compression and reconstruction based on GUI and Huffman coding." Journal of Physics: Conference Series 2580, no. 1 (2023): 012025. http://dx.doi.org/10.1088/1742-6596/2580/1/012025.

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Abstract Huffman coding is an important part of image compression technology, the image compression platform is based on GUI, and Huffman is also widely used. This paper introduces the basic principle of the Huffman algorithm, compares it with arithmetic coding and run length encoding, and expounds on the application of these three algorithms in JPEG compression. The AC algorithm combined block-based, fine texture models and adaptive arithmetic coding in the given an example. The RLE algorithm used automatic threshold, direction judgment, and selective value counts to improve its compression e
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Lamorahan, Christine, Benny Pinontoan, and Nelson Nainggolan. "Data Compression Using Shannon-Fano Algorithm." d'CARTESIAN 2, no. 2 (2013): 10. http://dx.doi.org/10.35799/dc.2.2.2013.3207.

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Abstract Communication systems in the world of technology, information and communication are known as data transfer system. Sometimes the information received lost its authenticity, because size of data to be transferred exceeds the capacity of the media used. This problem can be reduced by applying compression process to shrink the size of the data to obtain a smaller size. This study considers compression for data text using Shannon – Fano algorithm and shows how effective these algorithms in compressing it when compared with the Huffman algorithm. This research shows that text data compress
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Liu, Xing Ke, Ke Chen, and Bin Li. "Huffman Coding and Applications in Compression for Vector Maps." Applied Mechanics and Materials 333-335 (July 2013): 718–22. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.718.

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Huffman coding is a statistical lossless coding method with high efficiency. The principal and implementation of Huffman coding is discussed and Huffman coding is implemented to the compression of vector maps. The property of the algorithm is discussed. Experiments demonstrated that the algorithm proposed can compress vector maps with high efficiency and no loss.
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Fauzan, Mohamad Nurkamal, Muhammad Alif, and Cahyo Prianto3. "Comparison of Huffman Algorithm and Lempel Ziv Welch Algorithm in Text File Compression." IT Journal Research and Development 7, no. 2 (2022): 155–69. http://dx.doi.org/10.25299/itjrd.2023.10437.

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The development of data storage hardware is very rapidly over time. In line with the development of storage hardware, the amount of digital data shared on the internet is increasing every day. That way no matter how big the size of the storage device we have, of course, it will only be a matter of time until that storage space is exhausted. Therefore, in terms of maximizing storage space, a technique called compression emerged. This study focuses on a comparative analysis of 2 Lossless compression technique algorithms, namely the Huffman algorithm and Lempel Ziv Welch (LZW). A number of test f
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Dissertations / Theses on the topic "Huffman algorithm"

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Devulapalli, Venkata Lakshmi Narasimha. "Application of Huffman Data Compression Algorithm in Hashing Computation." TopSCHOLAR®, 2018. https://digitalcommons.wku.edu/theses/2614.

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Cryptography is the art of protecting information by encrypting the original message into an unreadable format. A cryptographic hash function is a hash function which takes an arbitrary length of the text message as input and converts that text into a fixed length of encrypted characters which is infeasible to invert. The values returned by the hash function are called as the message digest or simply hash values. Because of its versatility, hash functions are used in many applications such as message authentication, digital signatures, and password hashing [Thomsen and Knudsen, 2005]. The purp
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Le, Thu Anh. "An Exploration of the Word2vec Algorithm: Creating a Vector Representation of a Language Vocabulary that Encodes Meaning and Usage Patterns in the Vector Space Structure." Thesis, University of North Texas, 2016. https://digital.library.unt.edu/ark:/67531/metadc849728/.

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This thesis is an exloration and exposition of a highly efficient shallow neural network algorithm called word2vec, which was developed by T. Mikolov et al. in order to create vector representations of a language vocabulary such that information about the meaning and usage of the vocabulary words is encoded in the vector space structure. Chapter 1 introduces natural language processing, vector representations of language vocabularies, and the word2vec algorithm. Chapter 2 reviews the basic mathematical theory of deterministic convex optimization. Chapter 3 provides background on some concepts
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Maciel, Marcos Costa. "Compressão de dados ambientais em redes de sensores sem fio usando código de Huffman." Universidade Tecnológica Federal do Paraná, 2013. http://repositorio.utfpr.edu.br/jspui/handle/1/506.

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Fundação do Amparo à Pesquisa do Estado do Amazonas (FAPEAM)<br>Nesta dissertação de mestrado é apresentada uma proposta de um método simples de compressão de dados sem perda para Redes de Sensores sem Fio (RSSF). Este método é baseado numa codificação Huffman convencional aplicada a um conjunto de amostras de parâmetros monitorados que possuam uma forte correlação temporal, fazendo com que seja gerado um dicionário Huffman a partir dessas probabilidades e que possam ser utilizadas em outros conjuntos de parâmetros de mesma característica. Os resultados de simulação usando temperatura e umidad
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Хованська, Т. А. "Проблеми створення і стиснення великих інформаційних сховищ і складів даних". Master's thesis, Сумський державний університет, 2019. http://essuir.sumdu.edu.ua/handle/123456789/76429.

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Friedrich, Tomáš. "Komprese DNA sekvencí." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237222.

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The increasing volume of biological data requires finding new ways to save these data in genetic banks. The target of this work is design and implementation of a novel algorithm for compression of DNA sequences. The algorithm is based on aligning DNA sequences agains a reference sequence and storing only diferencies between sequence and reference model. The work contains basic prerequisities from molecular biology which are needed for understanding of algorithm details. Next aligment algorithms and common compress schemes suitable for storing of diferencies agains reference sequence are descri
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Dvořák, Martin. "Výukový video kodek." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219882.

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The first goal of diploma thesis is to study the basic principles of video signal compression. Introduction to techniques used to reduce irrelevancy and redundancy in the video signal. The second goal is, on the basis of information about compression tools, implement the individual compression tools in the programming environment of Matlab and assemble simple model of the video codec. Diploma thesis contains a description of the three basic blocks, namely - interframe coding, intraframe coding and coding with variable length word - according the standard MPEG-2.
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陳宏綜. "A Memory-Efficient and Fast Huffman Decoding Algorithm." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/64740387702559843977.

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碩士<br>國立臺灣科技大學<br>管理研究所資訊管理學程<br>87<br>To reduce the memory size and speed up the process of searching for a symbol in a Huffman tree, we propose a memory-efficient array data structure to represent the Huffman tree. Then, we present a fast Huffman decoding algorithm, which takes O(mlog n) time and uses 3n/2 + n/2logn + 1 memory space, where n is the number of symbols in a Huffman tree.
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Lin, Yi-Kai, and 林義凱. "A Space-Efficient Huffman Decoding Algorithm and its Parallelism." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/51208485736616000258.

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Lin, Yih-Kai, and 林義凱. "A Space-Efficient Huffman Decoding Algorithm and its Parallelism." Thesis, 1997. http://ndltd.ncl.edu.tw/handle/72819908164921559975.

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碩士<br>國立台灣工業技術學院<br>管理技術研究所<br>85<br>This paper first transforms the Huffman treeinto a single--side growing Huffman tree, then presents a memory--efficientdata structure to represent the single--side growing Huffman tree, whichrequires $O((n+d)\lceil \log_{2} n \rceil)$--bits memory space, where $n$ isthenumber of source symbols and $d$ is the depth of the Huffman tree.Based on the proposed data structure, we present an$O(d)$--timeHuffman decoding algorithm.Using the sameexample, thememory
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ho, Han-chang, and 何函璋. "A Fast Huffman Decoding Algorithm by Multiple Bit Length Search Scheme for the MPEG-4 AAC." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/04149818862470676859.

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碩士<br>國立成功大學<br>電機工程學系碩博士班<br>97<br>Huffman coding is an important part in MPEG-4 Advanced Audio Coding（AAC）standard. The function of Huffman coding is to encode the input data stream with shorter length of bit string so that the audio samples can be compressed into smaller size. The compressed data can be recovered by Huffman decoding in decoder side. The process of Huffman decoding requires long delay because long computational time is consumed by the excessive number of searches for the decoded symbols. In this paper, a fast Huffman decoding algorithm is proposed to reduce the number of se
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Books on the topic "Huffman algorithm"

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McSkane, Brian. The implementation of a Huffman compression algorithm for medical radiologic images in Khoros. The Author], 1996.

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Book chapters on the topic "Huffman algorithm"

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Liu, Yaqiong, Yuzhuo Wen, Dingrong Yuan, and Yuwei Cuan. "A Huffman Tree-Based Algorithm for Clustering Documents." In Advanced Data Mining and Applications. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-14717-8_49.

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Zhang, Yanhui, He Zhang, Jun Shi, and Xiaozheng Yin. "Microscan Imager Logging Data Compression Using improved Huffman Algorithm." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45049-9_101.

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Gupta, Mangalam, Dipanwita Sadhukhan, and Sangram Ray. "IBDNA – An Improved BDNA Algorithm Incorporating Huffman Coding Technique." In Proceedings of International Conference on Network Security and Blockchain Technology. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3182-6_11.

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Perl, Yehoshua, and Ashish Mehta. "Cascading LZW algorithm with huffman coding: A variable to variable length compression algorithm." In Computing in the 90's. Springer New York, 1991. http://dx.doi.org/10.1007/bfb0038489.

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Zhang, Wei, Yuejing Zhang, and Aiyun Zhan. "Zero-Tree Wavelet Algorithm Joint with Huffman Encoding for Image Compression." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-49017-4_11.

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Zhang, Ru, Jianyi Liu, and Feng Zhu. "A Steganography Algorithm Based on MP3 Linbits Bit of Huffman Codeword." In Advances in Intelligent Information Hiding and Multimedia Signal Processing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63859-1_22.

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Huo, Yonghua, Zhihao Wang, Junfang Wang, Kaiyang Qu, and Yang Yang. "An Adaptive Multiple Order Context Huffman Compression Algorithm Based on Markov Model." In Collaborate Computing: Networking, Applications and Worksharing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59288-6_8.

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Mohandass, Divya, and J. Janet. "An Improved Three Pattern Huffman Compression Algorithm for Medical Images in Telemedicine." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12214-9_43.

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Jeong, Wook-Hyun, and Yo-Sung Ho. "A New Construction Algorithm for Symmetrical Reversible Variable-Length Codes from the Huffman Code." In Computer and Information Sciences - ISCIS 2003. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-39737-3_84.

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Moffat, Alistair. "Huffman Coding." In Encyclopedia of Algorithms. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-2864-4_633.

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Conference papers on the topic "Huffman algorithm"

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Canpolat, Nida, Hasan Yetis, Orhan Yaman, and Mehmet Karakose. "Advanced Data Storage Model with Blockchain Technology and Huffman Algorithm." In 2025 29th International Conference on Information Technology (IT). IEEE, 2025. https://doi.org/10.1109/it64745.2025.10930257.

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Li, Wei, Zhen Peng Pang, and Zhi Jie Liu. "SPIHT Algorithm Combined with Huffman Encoding." In 2010 Third International Symposium on Intelligent Information Technology and Security Informatics (IITSI). IEEE, 2010. http://dx.doi.org/10.1109/iitsi.2010.63.

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Ya-Jun He, Duo-Li Zhang, Bin Shen, and Luo-Feng Geng. "Implementation of fast Huffman decoding algorithm." In 2007 7th International Conference on ASIC. IEEE, 2007. http://dx.doi.org/10.1109/icasic.2007.4415744.

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Ergude, Bao, Li Weisheng, Fan Dongrui, and Ma Xiaoyu. "A Study and Implementation of the Huffman Algorithm Based on Condensed Huffman Table." In 2008 International Conference on Computer Science and Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/csse.2008.1432.

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Vidhyaa, V. G., S. Aarthi Rajalakshmi, Ragavi Raghavan, G. S. V. Venu Gopal, and R. Gandhiraj. "Huffman encoding and decoding algorithm using IJulia." In 2016 International Conference on Communication and Signal Processing (ICCSP). IEEE, 2016. http://dx.doi.org/10.1109/iccsp.2016.7754207.

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Ao, Jun, Rui Li, and Chunbo Ma. "Improved MP3 Hiding Algorithm Based on Huffman Coding." In 2016 International Conference on Communications, Information Management and Network Security. Atlantis Press, 2016. http://dx.doi.org/10.2991/cimns-16.2016.57.

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Dhawale, Nidhi. "Implementation of Huffman algorithm and study for optimization." In 2014 International Conference on Advances in Communication and Computing Technologies (ICACACT). IEEE, 2014. http://dx.doi.org/10.1109/eic.2015.7230711.

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Pham, Hoang-Anh, Van-Hieu Bui, and Anh-Vu Dinh-Duc. "An Adaptive Huffman Decoding Algorithm for MP3 Decoder." In 2010 Fifth IEEE International Symposium on Electronic Design, Test & Applications. IEEE, 2010. http://dx.doi.org/10.1109/delta.2010.22.

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Hernandez, Marco Antonio Soto, Oscar Alvarado-Nava, Eduardo Rodriguez-Martinez, and Francisco J. Zaragoza Martinez. "Tree-less Huffman coding algorithm for embedded systems." In 2013 International Conference on ReConFigurable Computing and FPGAs (ReConFig). IEEE, 2013. http://dx.doi.org/10.1109/reconfig.2013.6732335.

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Milidiu, R. L., E. S. Laber, and A. A. Pessoa. "A work-efficient parallel algorithm for constructing Huffman codes." In Proceedings DCC'99 Data Compression Conference (Cat. No. PR00096). IEEE, 1999. http://dx.doi.org/10.1109/dcc.1999.755677.

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