Wikipedia

n-gram

For other uses, seeN-gram (disambiguation).
Not to be confused withword n-gram language modelorEngram.

Ann-gramis a sequence ofnadjacent symbols in particular order.[1]The symbols may benadjacentletters(includingpunctuation marksand blanks),syllables,or rarely wholewordsfound in a language dataset; or adjacentphonemesextracted from a speech-recording dataset, or adjacent base pairs extracted from a genome. They are collected from atext corpusorspeech corpus.

Sixn-grams frequently found in titles of publications about Coronavirus disease 2019 (COVID-19), as of 7 May 2020

N-gram is actually theparent of a family of namesterm, wherefamily memberscan be (depending onnnumeral) 1-gram, 2-gram etc., or the same using spoken numeral prefixes.

IfLatin numerical prefixesare used, thenn-gram of size 1 is called a "unigram", size 2 a "bigram"(or, less commonly, a" digram ") etc. If, instead of the Latin ones, theEnglish cardinal numbersare furtherly used, then they are called "four-gram", "five-gram", etc. Similarly, usingGreek numerical prefixessuch as "monomer", "dimer", "trimer", "tetramer", "pentamer", etc., or English cardinal numbers, "one-mer", "two-mer", "three-mer", etc. are used in computational biology, forpolymersoroligomersof a known size, calledk-mers.When the items are words,n-grams may also be calledshingles.[2]

In the context ofNatural language processing(NLP), the use ofn-grams allowsbag-of-wordsmodels to capture information such as word order, which would not be possible in the traditional bag of words setting.

Examples

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(Shannon 1951)[3]discussedn-gram models of English. For example:

  • 3-gram character model (random draw based on the probabilities of each trigram):in no ist lat whey cratict froure birs grocid pondenome of demonstures of the retagin is regiactiona of cre
  • 2-gram word model (random draw of words taking into account their transition probabilities):the head and in frontal attack on an english writer that the character of this point is therefore another method for the letters that the time of who ever told the problem for an unexpected
Figure 1n-gram examples from various disciplines
Field Unit Sample sequence 1-gram sequence 2-gram sequence 3-gram sequence
Vernacular name unigram bigram trigram
Order of resultingMarkov model 0 1 2
Protein sequencing amino acid ... Cys-Gly-Leu-Ser-Trp... ..., Cys, Gly, Leu, Ser, Trp,... ..., Cys-Gly, Gly-Leu, Leu-Ser, Ser-Trp,... ..., Cys-Gly-Leu, Gly-Leu-Ser, Leu-Ser-Trp,...
DNA sequencing base pair ...AGCTTCGA... ..., A, G, C, T, T, C, G, A,... ..., AG, GC, CT, TT, TC, CG, GA,... ..., AGC, GCT, CTT, TTC, TCG, CGA,...
Language model character ...to_be_or_not_to_be... ..., t, o, _, b, e, _, o, r, _, n, o, t, _, t, o, _, b, e,... ..., to, o_, _b, be, e_, _o, or, r_, _n, no, ot, t_, _t, to, o_, _b, be,... ..., to_, o_b, _be, be_, e_o, _or, or_, r_n, _no, not, ot_, t_t, _to, to_, o_b, _be,...
Wordn-gram language model word ... to be or not to be... ..., to, be, or, not, to, be,... ..., to be, be or, or not, not to, to be,... ..., to be or, be or not, or not to, not to be,...

Figure 1 shows several example sequences and the corresponding 1-gram, 2-gram and 3-gram sequences.

Here are further examples; these are word-level 3-grams and 4-grams (and counts of the number of times they appeared) from the Googlen-gram corpus.[4]

3-grams

  • ceramics collectables collectibles (55)
  • ceramics collectables fine (130)
  • ceramics collected by (52)
  • ceramics collectible pottery (50)
  • ceramics collectibles cooking (45)

4-grams

  • serve as the incoming (92)
  • serve as the incubator (99)
  • serve as the independent (794)
  • serve as the index (223)
  • serve as the indication (72)
  • serve as the indicator (120)

References

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  1. ^"n-gram language model - an overview | ScienceDirect Topics".sciencedirect.Retrieved12 December2024.
  2. ^Broder, Andrei Z.; Glassman, Steven C.; Manasse, Mark S.; Zweig, Geoffrey (1997). "Syntactic clustering of the web".Computer Networks and ISDN Systems.29(8):1157–1166.doi:10.1016/s0169-7552(97)00031-7.S2CID9022773.
  3. ^Shannon, Claude E. "The redundancy of English."Cybernetics; Transactions of the 7th Conference, New York: Josiah Macy, Jr. Foundation.1951.
  4. ^Franz, Alex; Brants, Thorsten (2006)."All OurN-gram are Belong to You ".Google Research Blog.Archivedfrom the original on 17 October 2006.Retrieved16 December2011.

Further reading

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See also

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