Package opennlp.tools.ngram
Class NGramUtils
- java.lang.Object
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- opennlp.tools.ngram.NGramUtils
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public class NGramUtils extends java.lang.Object
Utility class for ngrams. Some methods apply specifically to certain 'n' values, for e.g. tri/bi/uni-grams.
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Constructor Summary
Constructors Constructor Description NGramUtils()
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Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method Description static double
calculateBigramMLProbability(java.lang.String x0, java.lang.String x1, java.util.Collection<StringList> set)
calculate the probability of a bigram in a vocabulary using maximum likelihood estimationstatic double
calculateBigramPriorSmoothingProbability(java.lang.String x0, java.lang.String x1, java.util.Collection<StringList> set, java.lang.Double k)
calculate the probability of a bigram in a vocabulary using prior Laplace smoothing algorithmstatic double
calculateLaplaceSmoothingProbability(StringList ngram, java.lang.Iterable<StringList> set, java.lang.Double k)
calculate the probability of a ngram in a vocabulary using Laplace smoothing algorithmstatic double
calculateMissingNgramProbabilityMass(StringList ngram, java.lang.Double discount, java.lang.Iterable<StringList> set)
calculate the probability of a ngram in a vocabulary using the missing probability mass algorithmstatic double
calculateNgramMLProbability(StringList ngram, java.lang.Iterable<StringList> set)
calculate the probability of a ngram in a vocabulary using maximum likelihood estimationstatic double
calculateTrigramLinearInterpolationProbability(java.lang.String x0, java.lang.String x1, java.lang.String x2, java.util.Collection<StringList> set, java.lang.Double lambda1, java.lang.Double lambda2, java.lang.Double lambda3)
calculate the probability of a trigram in a vocabulary using a linear interpolation algorithmstatic double
calculateTrigramMLProbability(java.lang.String x0, java.lang.String x1, java.lang.String x2, java.lang.Iterable<StringList> set)
calculate the probability of a trigram in a vocabulary using maximum likelihood estimationstatic double
calculateUnigramMLProbability(java.lang.String word, java.util.Collection<StringList> set)
calculate the probability of a unigram in a vocabulary using maximum likelihood estimationstatic java.util.Collection<java.lang.String[]>
getNGrams(java.lang.String[] sequence, int size)
Get the ngrams of dimension n of a certain input sequence of tokens.static java.util.Collection<StringList>
getNGrams(StringList sequence, int size)
Get the ngrams of dimension n of a certain input sequence of tokens.static StringList
getNMinusOneTokenFirst(StringList ngram)
get the (n-1)th ngram of a given ngram, that is the same ngram except the last word in the ngramstatic StringList
getNMinusOneTokenLast(StringList ngram)
get the (n-1)th ngram of a given ngram, that is the same ngram except the first word in the ngram
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Method Detail
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calculateLaplaceSmoothingProbability
public static double calculateLaplaceSmoothingProbability(StringList ngram, java.lang.Iterable<StringList> set, java.lang.Double k)
calculate the probability of a ngram in a vocabulary using Laplace smoothing algorithm- Parameters:
ngram
- the ngram to get the probability forset
- the vocabularyk
- the smoothing factor- Returns:
- the Laplace smoothing probability
- See Also:
- Additive Smoothing
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calculateUnigramMLProbability
public static double calculateUnigramMLProbability(java.lang.String word, java.util.Collection<StringList> set)
calculate the probability of a unigram in a vocabulary using maximum likelihood estimation- Parameters:
word
- the only word in the unigramset
- the vocabulary- Returns:
- the maximum likelihood probability
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calculateBigramMLProbability
public static double calculateBigramMLProbability(java.lang.String x0, java.lang.String x1, java.util.Collection<StringList> set)
calculate the probability of a bigram in a vocabulary using maximum likelihood estimation- Parameters:
x0
- first word in the bigramx1
- second word in the bigramset
- the vocabulary- Returns:
- the maximum likelihood probability
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calculateTrigramMLProbability
public static double calculateTrigramMLProbability(java.lang.String x0, java.lang.String x1, java.lang.String x2, java.lang.Iterable<StringList> set)
calculate the probability of a trigram in a vocabulary using maximum likelihood estimation- Parameters:
x0
- first word in the trigramx1
- second word in the trigramx2
- third word in the trigramset
- the vocabulary- Returns:
- the maximum likelihood probability
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calculateNgramMLProbability
public static double calculateNgramMLProbability(StringList ngram, java.lang.Iterable<StringList> set)
calculate the probability of a ngram in a vocabulary using maximum likelihood estimation- Parameters:
ngram
- a ngramset
- the vocabulary- Returns:
- the maximum likelihood probability
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calculateBigramPriorSmoothingProbability
public static double calculateBigramPriorSmoothingProbability(java.lang.String x0, java.lang.String x1, java.util.Collection<StringList> set, java.lang.Double k)
calculate the probability of a bigram in a vocabulary using prior Laplace smoothing algorithm- Parameters:
x0
- the first word in the bigramx1
- the second word in the bigramset
- the vocabularyk
- the smoothing factor- Returns:
- the prior Laplace smoothiing probability
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calculateTrigramLinearInterpolationProbability
public static double calculateTrigramLinearInterpolationProbability(java.lang.String x0, java.lang.String x1, java.lang.String x2, java.util.Collection<StringList> set, java.lang.Double lambda1, java.lang.Double lambda2, java.lang.Double lambda3)
calculate the probability of a trigram in a vocabulary using a linear interpolation algorithm- Parameters:
x0
- the first word in the trigramx1
- the second word in the trigramx2
- the third word in the trigramset
- the vocabularylambda1
- trigram interpolation factorlambda2
- bigram interpolation factorlambda3
- unigram interpolation factor- Returns:
- the linear interpolation probability
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calculateMissingNgramProbabilityMass
public static double calculateMissingNgramProbabilityMass(StringList ngram, java.lang.Double discount, java.lang.Iterable<StringList> set)
calculate the probability of a ngram in a vocabulary using the missing probability mass algorithm- Parameters:
ngram
- the ngramdiscount
- discount factorset
- the vocabulary- Returns:
- the probability
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getNMinusOneTokenFirst
public static StringList getNMinusOneTokenFirst(StringList ngram)
get the (n-1)th ngram of a given ngram, that is the same ngram except the last word in the ngram- Parameters:
ngram
- a ngram- Returns:
- a ngram
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getNMinusOneTokenLast
public static StringList getNMinusOneTokenLast(StringList ngram)
get the (n-1)th ngram of a given ngram, that is the same ngram except the first word in the ngram- Parameters:
ngram
- a ngram- Returns:
- a ngram
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getNGrams
public static java.util.Collection<StringList> getNGrams(StringList sequence, int size)
Get the ngrams of dimension n of a certain input sequence of tokens.- Parameters:
sequence
- a sequence of tokenssize
- the size of the resulting ngrmams- Returns:
- all the possible ngrams of the given size derivable from the input sequence
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getNGrams
public static java.util.Collection<java.lang.String[]> getNGrams(java.lang.String[] sequence, int size)
Get the ngrams of dimension n of a certain input sequence of tokens.- Parameters:
sequence
- a sequence of tokenssize
- the size of the resulting ngrmams- Returns:
- all the possible ngrams of the given size derivable from the input sequence
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