Package org.apache.lucene.search.spell

Class DirectSpellChecker

  • public class DirectSpellChecker
extends java.lang.Object
    Simple automaton-based spellchecker.

    Candidates are presented directly from the term dictionary, based on Levenshtein distance. This is an alternative to SpellChecker if you are using an edit-distance-like metric such as Levenshtein or JaroWinklerDistance.

    A practical benefit of this spellchecker is that it requires no additional datastructures (neither in RAM nor on disk) to do its work.

    See Also:
    LevenshteinAutomata, FuzzyTermsEnum

    • Field Detail

      • INTERNAL_LEVENSHTEIN

        public static final StringDistance INTERNAL_LEVENSHTEIN
        The default StringDistance, Damerau-Levenshtein distance implemented internally via LevenshteinAutomata.

        Note: this is the fastest distance metric, because Damerau-Levenshtein is used to draw candidates from the term dictionary: this just re-uses the scoring.

    • Constructor Detail

      • DirectSpellChecker

        public DirectSpellChecker()
        Creates a DirectSpellChecker with default configuration values

    • Method Detail

      • getMaxEdits

        public int getMaxEdits()
        Get the maximum number of Levenshtein edit-distances to draw candidate terms from.

      • setMaxEdits

        public void setMaxEdits​(int maxEdits)
        Sets the maximum number of Levenshtein edit-distances to draw candidate terms from. This value can be 1 or 2. The default is 2.

        Note: a large number of spelling errors occur with an edit distance of 1, by setting this value to 1 you can increase both performance and precision at the cost of recall.

      • getMinPrefix

        public int getMinPrefix()
        Get the minimal number of characters that must match exactly

      • setMinPrefix

        public void setMinPrefix​(int minPrefix)
        Sets the minimal number of initial characters (default: 1) that must match exactly.

        This can improve both performance and accuracy of results, as misspellings are commonly not the first character.

      • getMaxInspections

        public int getMaxInspections()
        Get the maximum number of top-N inspections per suggestion

      • setMaxInspections

        public void setMaxInspections​(int maxInspections)
        Set the maximum number of top-N inspections (default: 5) per suggestion.

        Increasing this number can improve the accuracy of results, at the cost of performance.

      • getAccuracy

        public float getAccuracy()
        Get the minimal accuracy from the StringDistance for a match

      • setAccuracy

        public void setAccuracy​(float accuracy)
        Set the minimal accuracy required (default: 0.5f) from a StringDistance for a suggestion match.

      • getThresholdFrequency

        public float getThresholdFrequency()
        Get the minimal threshold of documents a term must appear for a match

      • setThresholdFrequency

        public void setThresholdFrequency​(float thresholdFrequency)
        Set the minimal threshold of documents a term must appear for a match.

        This can improve quality by only suggesting high-frequency terms. Note that very high values might decrease performance slightly, by forcing the spellchecker to draw more candidates from the term dictionary, but a practical value such as 1 can be very useful towards improving quality.

        This can be specified as a relative percentage of documents such as 0.5f, or it can be specified as an absolute whole document frequency, such as 4f. Absolute document frequencies may not be fractional.

      • getMinQueryLength

        public int getMinQueryLength()
        Get the minimum length of a query term needed to return suggestions

      • setMinQueryLength

        public void setMinQueryLength​(int minQueryLength)
        Set the minimum length of a query term (default: 4) needed to return suggestions.

        Very short query terms will often cause only bad suggestions with any distance metric.

      • getMaxQueryFrequency

        public float getMaxQueryFrequency()
        Get the maximum threshold of documents a query term can appear in order to provide suggestions.

      • setMaxQueryFrequency

        public void setMaxQueryFrequency​(float maxQueryFrequency)
        Set the maximum threshold (default: 0.01f) of documents a query term can appear in order to provide suggestions.

        Very high-frequency terms are typically spelled correctly. Additionally, this can increase performance as it will do no work for the common case of correctly-spelled input terms.

        This can be specified as a relative percentage of documents such as 0.5f, or it can be specified as an absolute whole document frequency, such as 4f. Absolute document frequencies may not be fractional.

      • getLowerCaseTerms

        public boolean getLowerCaseTerms()
        true if the spellchecker should lowercase terms

      • setLowerCaseTerms

        public void setLowerCaseTerms​(boolean lowerCaseTerms)
        True if the spellchecker should lowercase terms (default: true)

        This is a convenience method, if your index field has more complicated analysis (such as StandardTokenizer removing punctuation), its probably better to turn this off, and instead run your query terms through your Analyzer first.

        If this option is not on, case differences count as an edit!

      • getComparator

        public java.util.Comparator<SuggestWord> getComparator()
        Get the current comparator in use.

      • getDistance

        public StringDistance getDistance()
        Get the string distance metric in use.

      • setDistance

        public void setDistance​(StringDistance distance)
        Set the string distance metric. The default is INTERNAL_LEVENSHTEIN

        Note: because this spellchecker draws its candidates from the term dictionary using Damerau-Levenshtein, it works best with an edit-distance-like string metric. If you use a different metric than the default, you might want to consider increasing setMaxInspections(int) to draw more candidates for your metric to rank.

      • suggestSimilar

        public SuggestWord[] suggestSimilar​(Term term,
                                    int numSug,
                                    IndexReader ir,
                                    SuggestMode suggestMode,
                                    float accuracy)
                             throws java.io.IOException
        Suggest similar words.

        Unlike SpellChecker, the similarity used to fetch the most relevant terms is an edit distance, therefore typically a low value for numSug will work very well.

        Parameters:
        term - Term you want to spell check on
        numSug - the maximum number of suggested words
        ir - IndexReader to find terms from
        suggestMode - specifies when to return suggested words
        accuracy - return only suggested words that match with this similarity
        Returns:
        sorted list of the suggested words according to the comparator
        Throws:
        java.io.IOException - If there is a low-level I/O error.