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- Kneser–Ney_smoothing abstract "Kneser–Ney smoothing is a method primarily used to calculate the probability distribution of n-grams in a document based on their histories. It is widely considered the most effective method of smoothing due to its use of absolute discounting by subtracting a fixed value from the probability's lower order terms to omit n-grams with lower frequencies. This approach has been considered equally effective for both higher and lower order n-grams.A common example that illustrates the concept behind this method is the frequency of the bigram \"San Francisco\". If it appears several times in a training corpus, the frequency of the unigram \"Francisco\" will also be high. Relying on only the unigram frequency to predict the frequencies of n-grams leads to skewed results; however, Kneser–Ney smoothing corrects this by considering the frequency of the unigram in relation to possible words preceding it.".
- Kneser–Ney_smoothing wikiPageID "45391945".
- Kneser–Ney_smoothing wikiPageLength "2952".
- Kneser–Ney_smoothing wikiPageOutDegree "9".
- Kneser–Ney_smoothing wikiPageRevisionID "684529807".
- Kneser–Ney_smoothing wikiPageWikiLink Bigram.
- Kneser–Ney_smoothing wikiPageWikiLink Category:Statistics.
- Kneser–Ney_smoothing wikiPageWikiLink Document.
- Kneser–Ney_smoothing wikiPageWikiLink N-gram.
- Kneser–Ney_smoothing wikiPageWikiLink Probability.
- Kneser–Ney_smoothing wikiPageWikiLink San_Francisco.
- Kneser–Ney_smoothing wikiPageWikiLink Smoothing.
- Kneser–Ney_smoothing wikiPageWikiLink Text_corpus.
- Kneser–Ney_smoothing wikiPageWikiLinkText "Kneser–Ney smoothing".
- Kneser–Ney_smoothing wikiPageWikiLinkText "Kneser–Ney-smoothed".
- Kneser–Ney_smoothing wikiPageUsesTemplate Template:Probability-stub.
- Kneser–Ney_smoothing wikiPageUsesTemplate Template:Reflist.
- Kneser–Ney_smoothing subject Category:Statistics.
- Kneser–Ney_smoothing hypernym Method.
- Kneser–Ney_smoothing type Software.
- Kneser–Ney_smoothing comment "Kneser–Ney smoothing is a method primarily used to calculate the probability distribution of n-grams in a document based on their histories. It is widely considered the most effective method of smoothing due to its use of absolute discounting by subtracting a fixed value from the probability's lower order terms to omit n-grams with lower frequencies.".
- Kneser–Ney_smoothing label "Kneser–Ney smoothing".
- Kneser–Ney_smoothing sameAs Q19597638.
- Kneser–Ney_smoothing sameAs m.012vp2_n.
- Kneser–Ney_smoothing sameAs Q19597638.
- Kneser–Ney_smoothing wasDerivedFrom Kneser–Ney_smoothing?oldid=684529807.
- Kneser–Ney_smoothing isPrimaryTopicOf Kneser–Ney_smoothing.