Academic literature on the topic 'Text compression'
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Journal articles on the topic "Text compression"
Divakaran, Sajilal, Biji C. L., Anjali C, and Achuthsankar S. Nair. "MALAYALAM TEXT COMPRESSION." International Journal of Information Systems and Engineering 1, no. 1 (April 30, 2013): 1–11. http://dx.doi.org/10.24924/ijise/2013.04/v1.iss1/1.11.
Full textDavison, Andrew. "Vague text compression." ACM SIGACT News 24, no. 1 (January 15, 1993): 68–74. http://dx.doi.org/10.1145/152992.153009.
Full textBol'shakov, I. A., and A. V. Smirnov. "Text compression methods." Journal of Soviet Mathematics 56, no. 1 (August 1991): 2249–62. http://dx.doi.org/10.1007/bf01099202.
Full textMurugesan, G., and Rosario Gilmary. "Compression of text files using genomic code compression algorithm." International Journal of Engineering & Technology 7, no. 2.31 (May 29, 2018): 69. http://dx.doi.org/10.14419/ijet.v7i2.31.13399.
Full textP, Srividya. "Optimization of Lossless Compression Algorithms using Multithreading." Journal of Information Technology and Sciences 9, no. 1 (March 2, 2023): 36–42. http://dx.doi.org/10.46610/joits.2022.v09i01.005.
Full textStecuła, Beniamin, Kinga Stecuła, and Adrian Kapczyński. "Compression of Text in Selected Languages—Efficiency, Volume, and Time Comparison." Sensors 22, no. 17 (August 25, 2022): 6393. http://dx.doi.org/10.3390/s22176393.
Full textNguyen, Vu H., Hien T. Nguyen, Hieu N. Duong, and Vaclav Snasel. "n-Gram-Based Text Compression." Computational Intelligence and Neuroscience 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/9483646.
Full textOmer. "Arabic Short Text Compression." Journal of Computer Science 6, no. 1 (January 1, 2010): 24–28. http://dx.doi.org/10.3844/jcssp.2010.24.28.
Full textKAUFMAN, YAIR, and SHMUEL T. KLEIN. "SEMI-LOSSLESS TEXT COMPRESSION." International Journal of Foundations of Computer Science 16, no. 06 (December 2005): 1167–78. http://dx.doi.org/10.1142/s012905410500373x.
Full textman, Suher, and Andysah Putera Utama Siahaan. "Huffman Text Compression Technique." International Journal of Computer Science and Engineering 3, no. 8 (August 25, 2016): 103–8. http://dx.doi.org/10.14445/23488387/ijcse-v3i8p124.
Full textDissertations / Theses on the topic "Text compression"
Wilson, Timothy David. "Animation of text compression algorithms." Thesis, University of Canterbury. Computer Science, 1992. http://hdl.handle.net/10092/9570.
Full textBranavan, Satchuthananthavale Rasiah Kuhan. "High compression rate text summarization." Thesis, Massachusetts Institute of Technology, 2008. http://hdl.handle.net/1721.1/44368.
Full textIncludes bibliographical references (p. 95-97).
This thesis focuses on methods for condensing large documents into highly concise summaries, achieving compression rates on par with human writers. While the need for such summaries in the current age of information overload is increasing, the desired compression rate has thus far been beyond the reach of automatic summarization systems. The potency of our summarization methods is due to their in-depth modelling of document content in a probabilistic framework. We explore two types of document representation that capture orthogonal aspects of text content. The first represents the semantic properties mentioned in a document in a hierarchical Bayesian model. This method is used to summarize thousands of consumer reviews by identifying the product properties mentioned by multiple reviewers. The second representation captures discourse properties, modelling the connections between different segments of a document. This discriminatively trained model is employed to generate tables of contents for books and lecture transcripts. The summarization methods presented here have been incorporated into large-scale practical systems that help users effectively access information online.
by Satchuthananthavale Rasiah Kuhan Branavan.
S.M.
Langiu, Alessio. "Optimal Parsing for dictionary text compression." Thesis, Paris Est, 2012. http://www.theses.fr/2012PEST1091/document.
Full textDictionary-based compression algorithms include a parsing strategy to transform the input text into a sequence of dictionary phrases. Given a text, such process usually is not unique and, for compression purpose, it makes sense to find one of the possible parsing that minimizes the final compression ratio. This is the parsing problem. An optimal parsing is a parsing strategy or a parsing algorithm that solve the parsing problem taking account of all the constraints of a compression algorithm or of a class of homogeneous compression algorithms. Compression algorithm constrains are, for instance, the dictionary itself, i.e. the dynamic set of available phrases, and how much a phrase weight on the compressed text, i.e. the length of the codeword that represent such phrase also denoted as the cost of a dictionary pointer encoding. In more than 30th years of history of dictionary based text compression, while plenty of algorithms, variants and extensions appeared and while such approach to text compression become one of the most appreciated and utilized in almost all the storage and communication process, only few optimal parsing algorithms was presented. Many compression algorithms still leaks optimality of their parsing or, at least, proof of optimality. This happens because there is not a general model of the parsing problem that includes all the dictionary based algorithms and because the existing optimal parsings work under too restrictive hypothesis. This work focus on the parsing problem and presents both a general model for dictionary based text compression called Dictionary-Symbolwise theory and a general parsing algorithm that is proved to be optimal under some realistic hypothesis. This algorithm is called Dictionary-Symbolwise Flexible Parsing and it covers almost all the cases of dictionary based text compression algorithms together with the large class of their variants where the text is decomposed in a sequence of symbols and dictionary phrases.In this work we further consider the case of a free mixture of a dictionary compressor and a symbolwise compressor. Our Dictionary-Symbolwise Flexible Parsing covers also this case. We have indeed an optimal parsing algorithm in the case of dictionary-symbolwise compression where the dictionary is prefix closed and the cost of encoding dictionary pointer is variable. The symbolwise compressor is any classical one that works in linear time, as many common variable-length encoders do. Our algorithm works under the assumption that a special graph that will be described in the following, is well defined. Even if this condition is not satisfied it is possible to use the same method to obtain almost optimal parses. In detail, when the dictionary is LZ78-like, we show how to implement our algorithm in linear time. When the dictionary is LZ77-like our algorithm can be implemented in time O(n log n). Both have O(n) space complexity. Even if the main aim of this work is of theoretical nature, some experimental results will be introduced to underline some practical effects of the parsing optimality in compression performance and some more detailed experiments are hosted in a devoted appendix
Ong, Ghim Hwee. "Text compression for transmission and storage." Thesis, Loughborough University, 1989. https://dspace.lboro.ac.uk/2134/13790.
Full textJones, Greg 1963-2017. "RADIX 95n: Binary-to-Text Data Conversion." Thesis, University of North Texas, 1991. https://digital.library.unt.edu/ark:/67531/metadc500582/.
Full textHe, Meng. "Indexing Compressed Text." Thesis, University of Waterloo, 2003. http://hdl.handle.net/10012/1143.
Full textBlandon, Julio Cesar. "A novel lossless compression technique for text data." FIU Digital Commons, 1999. http://digitalcommons.fiu.edu/etd/1694.
Full textThaper, Nitin 1975. "Using compression for source-based classification of text." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/86595.
Full textZhang, Nan. "TRANSFORM BASED AND SEARCH AWARE TEXT COMPRESSION SCHEMES AND COMPRESSED DOMAIN TEXT RETRIEVAL." Doctoral diss., University of Central Florida, 2005. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/3938.
Full textPh.D.
School of Computer Science
Engineering and Computer Science
Computer Science
Linhares, Pontes Elvys. "Compressive Cross-Language Text Summarization." Thesis, Avignon, 2018. http://www.theses.fr/2018AVIG0232/document.
Full textThe popularization of social networks and digital documents increased quickly the informationavailable on the Internet. However, this huge amount of data cannot be analyzedmanually. Natural Language Processing (NLP) analyzes the interactions betweencomputers and human languages in order to process and to analyze natural languagedata. NLP techniques incorporate a variety of methods, including linguistics, semanticsand statistics to extract entities, relationships and understand a document. Amongseveral NLP applications, we are interested, in this thesis, in the cross-language textsummarization which produces a summary in a language different from the languageof the source documents. We also analyzed other NLP tasks (word encoding representation,semantic similarity, sentence and multi-sentence compression) to generate morestable and informative cross-lingual summaries.Most of NLP applications (including all types of text summarization) use a kind ofsimilarity measure to analyze and to compare the meaning of words, chunks, sentencesand texts in their approaches. A way to analyze this similarity is to generate a representationfor these sentences that contains the meaning of them. The meaning of sentencesis defined by several elements, such as the context of words and expressions, the orderof words and the previous information. Simple metrics, such as cosine metric andEuclidean distance, provide a measure of similarity between two sentences; however,they do not analyze the order of words or multi-words. Analyzing these problems,we propose a neural network model that combines recurrent and convolutional neuralnetworks to estimate the semantic similarity of a pair of sentences (or texts) based onthe local and general contexts of words. Our model predicted better similarity scoresthan baselines by analyzing better the local and the general meanings of words andmulti-word expressions.In order to remove redundancies and non-relevant information of similar sentences,we propose a multi-sentence compression method that compresses similar sentencesby fusing them in correct and short compressions that contain the main information ofthese similar sentences. We model clusters of similar sentences as word graphs. Then,we apply an integer linear programming model that guides the compression of theseclusters based on a list of keywords. We look for a path in the word graph that has goodcohesion and contains the maximum of keywords. Our approach outperformed baselinesby generating more informative and correct compressions for French, Portugueseand Spanish languages. Finally, we combine these previous methods to build a cross-language text summarizationsystem. Our system is an {English, French, Portuguese, Spanish}-to-{English,French} cross-language text summarization framework that analyzes the informationin both languages to identify the most relevant sentences. Inspired by the compressivetext summarization methods in monolingual analysis, we adapt our multi-sentencecompression method for this problem to just keep the main information. Our systemproves to be a good alternative to compress redundant information and to preserve relevantinformation. Our system improves informativeness scores without losing grammaticalquality for French-to-English cross-lingual summaries. Analyzing {English,French, Portuguese, Spanish}-to-{English, French} cross-lingual summaries, our systemsignificantly outperforms extractive baselines in the state of the art for all these languages.In addition, we analyze the cross-language text summarization of transcriptdocuments. Our approach achieved better and more stable scores even for these documentsthat have grammatical errors and missing information
Books on the topic "Text compression"
Bell, Timothy C. Text compression. Englewood Cliffs, N.J: Prentice Hall, 1990.
Find full textStorer, James A. Image and Text Compression. Boston, MA: Springer US, 1992.
Find full textStorer, James A., ed. Image and Text Compression. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4615-3596-6.
Full text1953-, Storer James A., ed. Image and text compression. Boston: Kluwer Academic, 1992.
Find full textD, Barni Mauro Ph, ed. Document and image compression. Boca Raton, FL: CRC/Taylor & Francis, 2006.
Find full textAlistair, Moffat, and Bell Timothy C, eds. Managing gigabytes: Compressing and indexing documents and images. New York: Van Nostrand Reinhold, 1994.
Find full textSabourin, Conrad. Computational character processing: Character coding, input, output, synthesis, ordering, conversion, text compression, encryption, display hashing, literate programming : bibliography. Montréal: Infolingua, 1994.
Find full textSabourin, Conrad. Computational speech processing: Speech analysis, recognition, understanding, compression, transmission, coding, synthesis, text to speech systems, speech to tactile displays, speaker identification, prosody processing : bibliography. Montréal: Infolingua, 1994.
Find full textCold Regions Research and Engineering Laboratory (U.S.), ed. Axial double-ball test versus the uniaxial unconfined compression test for measuring the compressive strength of freshwater and sea ice. [Hanover, N.H.]: US Army Corps of Engineers, Cold Regions Research & Engineering Laboratory, 1993.
Find full textDavis, Randall C. Analysis and test of superplastically formed titanium hat-stiffened panels under compression. [S.l.]: [s.n.], 1986.
Find full textBook chapters on the topic "Text compression"
Ferragina, Paolo Igor, and Igor Nitto. "Text Compression." In Encyclopedia of Database Systems, 3046–48. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_1151.
Full textFerragina, Paolo, Igor Nitto, and Rossano Venturini. "Text Compression." In Encyclopedia of Database Systems, 1–3. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_1151-2.
Full textFerragina, Paolo, Igor Nitto, and Rossano Venturini. "Text Compression." In Encyclopedia of Database Systems, 4070–72. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_1151.
Full textKonow, Roberto, and Gonzalo Navarro. "Text Index Compression." In Encyclopedia of Database Systems, 1–6. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4899-7993-3_945-2.
Full textNavarro, Gonzalo. "Text Index Compression." In Encyclopedia of Database Systems, 3051–55. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_945.
Full textKonow, Roberto, and Gonzalo Navarro. "Text Index Compression." In Encyclopedia of Database Systems, 4075–81. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_945.
Full textMandal, Mrinal Kr. "Text Representation and Compression." In Multimedia Signals and Systems, 121–44. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0265-4_6.
Full textCrochemore, M., F. Mignosi, A. Restivo, and S. Salemi. "Text Compression Using Antidictionaries." In Automata, Languages and Programming, 261–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48523-6_23.
Full textPalaniappan, Venka, and Shahram Latifi. "Lossy Text Compression Techniques." In ICCS 2007, 205–10. London: Springer London, 2007. http://dx.doi.org/10.1007/978-1-84628-992-7_28.
Full textMolina, Alejandro, Juan-Manuel Torres-Moreno, Eric SanJuan, Iria da Cunha, and Gerardo Eugenio Sierra Martínez. "Discursive Sentence Compression." In Computational Linguistics and Intelligent Text Processing, 394–407. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37256-8_33.
Full textConference papers on the topic "Text compression"
Gowtham, S., G. Iyshwarya, Kaushik Veluru, A. Tamarai Selvi, and J. Vasudha. "Text compression using ambigrams." In 2010 2nd International Conference on Education Technology and Computer (ICETC). IEEE, 2010. http://dx.doi.org/10.1109/icetc.2010.5529630.
Full textTeuhola, Jukka, and Timo Raita. "Text compression using prediction." In the 9th annual international ACM SIGIR conference. New York, New York, USA: ACM Press, 1986. http://dx.doi.org/10.1145/253168.253192.
Full textGoksu, Hayriye, and Banu Diri. "Morphology based text compression." In 2010 IEEE 18th Signal Processing and Communications Applications Conference (SIU 2010). IEEE, 2010. http://dx.doi.org/10.1109/siu.2010.5651231.
Full textMoore, John P. T., Antonio D. Kheirkhahzadeh, and Jiva N. Bagale. "Towards Markup-Aware Text Compression." In 2014 Data Compression Conference (DCC). IEEE, 2014. http://dx.doi.org/10.1109/dcc.2014.80.
Full textBille, Philip, Mikko Berggren Ettienne, Travis Gagie, Inge Li Gortz, and Nicola Prezza. "Decompressing Lempel-Ziv Compressed Text." In 2020 Data Compression Conference (DCC). IEEE, 2020. http://dx.doi.org/10.1109/dcc47342.2020.00022.
Full textKruse, H., and A. Mukherjee. "Data compression using text encryption." In Proceedings DCC '97. Data Compression Conference. IEEE, 1997. http://dx.doi.org/10.1109/dcc.1997.582107.
Full textSatoh, N., T. Morihara, Y. Okada, and S. Yoshida. "Study of Japanese text compression." In Proceedings DCC '97. Data Compression Conference. IEEE, 1997. http://dx.doi.org/10.1109/dcc.1997.582134.
Full textSeker, Abdulkadir, Emre Delibas, and Banu Diri. "DNA sequence compression within traditional text compression algorithms." In 2017 25th Signal Processing and Communications Applications Conference (SIU). IEEE, 2017. http://dx.doi.org/10.1109/siu.2017.7960193.
Full textFenwick, P. "Symbol ranking text compressors." In Proceedings DCC '97. Data Compression Conference. IEEE, 1997. http://dx.doi.org/10.1109/dcc.1997.582093.
Full textRajesh, Bulla, Mohammed Javed, P. Nagabhushan, and Watanabe Osamu. "Segmentation of Text-Lines and Words from JPEG Compressed Printed Text Documents Using DCT Coefficients." In 2020 Data Compression Conference (DCC). IEEE, 2020. http://dx.doi.org/10.1109/dcc47342.2020.00083.
Full textReports on the topic "Text compression"
Trim, M., Matthew Murray, and C. Crane. Modernization and structural evaluation of the improved Overhead Cable System. Engineer Research and Development Center (U.S.), March 2021. http://dx.doi.org/10.21079/11681/40025.
Full textKovacs, Austin. Axial Double-Ball Test Versus the Uniaxial Unconfined Compression Test for Measuring the Compressive Strength of Freshwater and Sea Ice. Fort Belvoir, VA: Defense Technical Information Center, December 1993. http://dx.doi.org/10.21236/ada277025.
Full textCorona, Edmundo. Numerical Simulations of the Kolsky Compression Bar Test. Office of Scientific and Technical Information (OSTI), October 2015. http://dx.doi.org/10.2172/1226520.
Full textJadaan, Osama M., and Andrew A. Wereszczak. Effective Size Analysis of the Diametral Compression (Brazil) Test Specimen. Office of Scientific and Technical Information (OSTI), April 2009. http://dx.doi.org/10.2172/951944.
Full textDyer, S., A. Faburada, K. Gallavan, M. Hoogendyk, and P. Hui. Compression Strength and Drop Test Performance of XM232 Case Assemblies,. Fort Belvoir, VA: Defense Technical Information Center, December 1995. http://dx.doi.org/10.21236/ada303269.
Full textShrestha, Som, Vishaldeep Sharma, and Omar Abdelaziz. Test Report #33: Compressor Calorimeter Test of R-410A Alternative: R-32/R-134a Mixture Using a Scroll Compressor. Office of Scientific and Technical Information (OSTI), February 2014. http://dx.doi.org/10.2172/1130959.
Full textTantawi, Sami. The Next Linear Collider Test Accelerator's RF Pulse Compression and Transmission Systems. Office of Scientific and Technical Information (OSTI), February 1999. http://dx.doi.org/10.2172/10192.
Full textShrestha, Som S., Vishaldeep Sharma, and Omar Abdelaziz. Compressor Calorimeter Test of R-410A Alternative: R-32/134a Mixture Using a Scroll Compressor. Office of Scientific and Technical Information (OSTI), February 2014. http://dx.doi.org/10.2172/1131502.
Full textCroop, Harold C. Fabrication of Curved Graphite/Epoxy Compression Test Panels and Generation of Material Properties. Fort Belvoir, VA: Defense Technical Information Center, October 1985. http://dx.doi.org/10.21236/ada368444.
Full textBaral, Aniruddha, Jeffrey Roesler, M. Ley, Shinhyu Kang, Loren Emerson, Zane Lloyd, Braden Boyd, and Marllon Cook. High-volume Fly Ash Concrete for Pavements Findings: Volume 1. Illinois Center for Transportation, September 2021. http://dx.doi.org/10.36501/0197-9191/21-030.
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