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prediction by partial matching wikipedia jump to content main menu main menu move to sidebar hide navigation main page contents current events random article about wikipedia contact us contribute help learn to edit community portal recent changes upload file special pages search search appearance donate create account log in personal tools donate create account log in contents move to sidebar hide top 1 theory 2 implementation 3 see also 4 sources 5 references toggle the table of contents prediction by partial matching 8 languages deutsch español français italiano 日本語 polski русский українська edit links article talk english read edit view history tools tools move to sidebar hide actions read edit view history general what links here related changes upload file permanent link page information cite this page get shortened url switch to legacy parser print export download as pdf printable version in other projects wikidata item appearance move to sidebar hide from wikipedia the free encyclopedia data compression technique ppmd redirects here for the american professional esports player see ppmd this article includes a list of general references but lacks sufficient corresponding inline citations please help improve this article by introducing more precise citations november 2015 learn how and when to remove this message prediction by partial matching ppm is an adaptive statistical data compression technique based on context modeling and prediction ppm models use a set of previous symbols in the uncompressed symbol stream to predict the next symbol in the stream ppm algorithms can also be used to cluster data into predicted groupings in cluster analysis theory edit predictions are usually reduced to symbol rankings clarification needed each symbol a letter bit or any other amount of data is ranked before it is compressed and the ranking system determines the corresponding codeword and therefore the compression rate in many compression algorithms the ranking is equivalent to probability mass function estimation given the previous letters or given a context each symbol is assigned with a probability for instance in arithmetic coding the symbols are ranked by their probabilities to appear after previous symbols and the whole sequence is compressed into a single fraction that is computed according to these probabilities the number of previous symbols n determines the order of the ppm model which is denoted as ppm n unbounded variants where the context has no length limitations also exist and are denoted as ppm if no prediction can be made based on all n context symbols a prediction is attempted with n 1 symbols this process is repeated until a match is found or no more symbols remain in context at that point a fixed prediction is made much of the work in optimizing a ppm model is handling inputs that have not already occurred in the input stream the obvious way to handle them is to create a never seen symbol which triggers the escape sequence clarification needed but what probability should be assigned to a symbol that has never been seen this is called the zero frequency problem one variant uses the laplace estimator which assigns the never seen symbol a fixed pseudocount of one a variant called ppmd increments the pseudocount of the never seen symbol every time the never seen symbol is used in other words ppmd estimates the probability of a new symbol as the ratio of the number of unique symbols to the total number of symbols observed implementation edit ppm compression implementations vary greatly in other details the actual symbol selection is usually recorded using arithmetic coding though it is also possible to use huffman encoding or even some type of dictionary coding technique the underlying model used in most ppm algorithms can also be extended to predict multiple symbols it is also possible to use non markov modeling to either replace or supplement markov modeling the symbol size is usually static typically a single byte which makes generic handling of any file format easy the ppm family of algorithms originated with work by john g cleary and ian h witten who described adaptive coding using partial string matching in 1984 their experiments reported compression of mixed case english text to as little as 2 2 bits per character 1 ai generated verification needed ppmd is a public domain implementation of ppmii ppm with information inheritance by dmitry shkarin which has undergone several incompatible revisions 2 it is used in the rar file format by default it is also available in the 7z and zip file formats attempts to improve ppm algorithms led to the paq series of data compression algorithms a ppm algorithm rather than being used for compression is used to increase the efficiency of user input in the alternate input method program dasher see also edit language model n gram sources edit cleary j witten i april 1984 data compression using adaptive coding and partial string matching ieee trans commun 32 4 396 402 citeseerx 10 1 1 14 4305 doi 10 1109 tcom 1984 1096090 cite journal cite uses deprecated parameter citeseerx help moffat a november 1990 implementing the ppm data compression scheme ieee trans commun 38 11 1917 1921 citeseerx 10 1 1 120 8728 doi 10 1109 26 61469 cite journal cite uses deprecated parameter citeseerx help cleary j g teahan w j witten i h 1997 unbounded length contexts for ppm the computer journal 40 2_and_3 oxford england oxford university press 67 75 doi 10 1093 comjnl 40 2_and_3 67 issn 0010 4620 c bloom solving the problems of context modeling w j teahan probability estimation for ppm original source from archive org schürmann t grassberger p september 1996 entropy estimation of symbol sequences chaos 6 3 414 427 arxiv cond mat 0203436 bibcode 1996chaos 6 414s doi 10 1063 1 166191 pmid 12780271 s2cid 10090433 references edit cleary john g witten ian h april 1984 data compression using adaptive coding and partial string matching ieee transactions on communications 32 4 396 402 doi 10 1109 tcom 1984 1096090 bmf ppmd всё о сжатии данных изображений и видео compression ru in russian note requires manually setting the cyrillic windows encoding in browser v t e data compression methods lossless type entropy adaptive coding arithmetic asymmetric numeral systems golomb huffman adaptive canonical modified range shannon shannon fano shannon fano elias tunstall unary universal exp golomb fibonacci gamma levenshtein dictionary byte pair encoding lempel ziv 842 lz4 lzjb lzo lzrw lzss lzw lzwl snappy other bwt ctw cm delta incremental dmc dpcm grammar re pair sequitur ldct mtf paq ppm rle hybrid lz77 huffman deflate lzx lzs lz77 ans lzfse lz77 huffman ans zstandard lz77 huffman context brotli lzss huffman lha lzh lz77 range lzma lzham rle bwt mtf huffman bzip2 lossy type transform discrete cosine transform dct mdct dst fft wavelet daubechies dwt spiht predictive dpcm adpcm lpc acelp celp lar lsp wlpc motion compensation estimation vector psychoacoustic audio concepts bit rate abr cbr vbr companding convolution dynamic range latency nyquist shannon theorem sampling silence compression sound quality speech coding sub band coding codec parts a law μ law dpcm adpcm dm ft fft lpc acelp celp lar lsp wlpc mdct psychoacoustic model image concepts chroma subsampling coding tree unit color space compression artifact image resolution macroblock pixel psnr quantization standard test image texture compression methods chain code dct deflate fractal klt lp rle wavelet daubechies dwt ezw spiht video concepts bit rate abr cbr vbr display resolution frame frame rate frame types interlace video characteristics video quality codec parts dct dpcm deblocking filter lapped transform motion compensation estimation vector wavelet daubechies dwt theory compressed data structures compressed suffix array fm index entropy information theory timeline kolmogorov complexity prefix code quantization rate distortion redundancy symmetry smallest grammar problem community hutter prize people mark adler david a huffman phil katz retrieved from https en wikipedia org w index php title prediction_by_partial_matching oldid 1375046827 categories lossless compression algorithms data compression hidden categories articles with short description short description is different from wikidata articles lacking in text citations from november 2015 all articles lacking in text citations wikipedia articles needing clarification from november 2016 articles containing suspected ai generated texts from september 2026 all pages needing factual verification wikipedia articles needing factual verification from september 2026 cs1 russian language sources ru cs1 errors deprecated parameters this page was last edited on 15 september 2026 at 15 02 utc page was rendered with parsoid text is available under the creative commons attribution sharealike 4 0 license additional terms may apply by using this site you agree to the terms of use and privacy policy 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