Class FuzzyQuery

Implements the fuzzy search query. The similarity measurement is based on the Damerau-Levenshtein (optimal string alignment) algorithm, though you can explicitly choose classic Levenshtein by passing false to the transpositions parameter.

this query uses MultiTermQuery.TopTermsScoringBooleanQueryRewrite as default. So terms will be collected and scored according to their edit distance. Only the top terms are used for building the BooleanQuery. It is not recommended to change the rewrite mode for fuzzy queries.

At most, this query will match terms up to MAXIMUM_SUPPORTED_DISTANCE edits. Higher distances (especially with transpositions enabled), are generally not useful and will match a significant amount of the term dictionary. If you really want this, consider using an n-gram indexing technique (such as the SpellChecker in the suggest module) instead.

NOTE: terms of length 1 or 2 will sometimes not match because of how the scaled distance between two terms is computed. For a term to match, the edit distance between the terms must be less than the minimum length term (either the input term, or the candidate term). For example, FuzzyQuery on term "abcd" with maxEdits=2 will not match an indexed term "ab", and FuzzyQuery on term "a" with maxEdits=2 will not match an indexed term "abc".

Inheritance

object

Query

MultiTermQuery

FuzzyQuery

Inherited Members

MultiTermQuery.m_field

MultiTermQuery.m_rewriteMethod

MultiTermQuery.CONSTANT_SCORE_FILTER_REWRITE

MultiTermQuery.SCORING_BOOLEAN_QUERY_REWRITE

MultiTermQuery.CONSTANT_SCORE_BOOLEAN_QUERY_REWRITE

MultiTermQuery.CONSTANT_SCORE_AUTO_REWRITE_DEFAULT

MultiTermQuery.Field

MultiTermQuery.GetTermsEnum(Terms)

MultiTermQuery.Rewrite(IndexReader)

MultiTermQuery.MultiTermRewriteMethod

Query.Boost

Query.ToString()

Query.CreateWeight(IndexSearcher)

Query.ExtractTerms(ISet<Term>)

Query.Clone()

object.Equals(object, object)

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

Namespace: Lucene.Net.Search

Assembly: Lucene.Net.dll

Syntax

public class FuzzyQuery : MultiTermQuery

Constructors

FuzzyQuery(Term)

Calls FuzzyQuery(term, defaultMaxEdits).

Declaration

public FuzzyQuery(Term term)

Parameters

Type	Name	Description
Term	term

FuzzyQuery(Term, int)

Calls FuzzyQuery(term, maxEdits, defaultPrefixLength).

Declaration

public FuzzyQuery(Term term, int maxEdits)

Parameters

Type	Name	Description
Term	term
int	maxEdits

FuzzyQuery(Term, int, int)

Calls FuzzyQuery(term, maxEdits, prefixLength, defaultMaxExpansions, defaultTranspositions).

Declaration

public FuzzyQuery(Term term, int maxEdits, int prefixLength)

Parameters

Type	Name	Description
Term	term
int	maxEdits
int	prefixLength

FuzzyQuery(Term, int, int, int, bool)

Create a new FuzzyQuery that will match terms with an edit distance of at most maxEdits to term. If a prefixLength > 0 is specified, a common prefix of that length is also required.

Declaration

public FuzzyQuery(Term term, int maxEdits, int prefixLength, int maxExpansions, bool transpositions)

Parameters

Type	Name	Description
Term	term	The term to search for
int	maxEdits	Must be >= 0 and <= MAXIMUM_SUPPORTED_DISTANCE.
int	prefixLength	Length of common (non-fuzzy) prefix
int	maxExpansions	The maximum number of terms to match. If this number is greater than MaxClauseCount when the query is rewritten, then the maxClauseCount will be used instead.
bool	transpositions	true if transpositions should be treated as a primitive edit operation. If this is false, comparisons will implement the classic Levenshtein algorithm.

Fields

DefaultMaxEdits

Implements the fuzzy search query. The similarity measurement is based on the Damerau-Levenshtein (optimal string alignment) algorithm, though you can explicitly choose classic Levenshtein by passing false to the transpositions parameter.

this query uses MultiTermQuery.TopTermsScoringBooleanQueryRewrite as default. So terms will be collected and scored according to their edit distance. Only the top terms are used for building the BooleanQuery. It is not recommended to change the rewrite mode for fuzzy queries.

At most, this query will match terms up to MAXIMUM_SUPPORTED_DISTANCE edits. Higher distances (especially with transpositions enabled), are generally not useful and will match a significant amount of the term dictionary. If you really want this, consider using an n-gram indexing technique (such as the SpellChecker in the suggest module) instead.

NOTE: terms of length 1 or 2 will sometimes not match because of how the scaled distance between two terms is computed. For a term to match, the edit distance between the terms must be less than the minimum length term (either the input term, or the candidate term). For example, FuzzyQuery on term "abcd" with maxEdits=2 will not match an indexed term "ab", and FuzzyQuery on term "a" with maxEdits=2 will not match an indexed term "abc".

Declaration

public const int DefaultMaxEdits = 2

Field Value

Type	Description
int

DefaultMaxExpansions

Implements the fuzzy search query. The similarity measurement is based on the Damerau-Levenshtein (optimal string alignment) algorithm, though you can explicitly choose classic Levenshtein by passing false to the transpositions parameter.

this query uses MultiTermQuery.TopTermsScoringBooleanQueryRewrite as default. So terms will be collected and scored according to their edit distance. Only the top terms are used for building the BooleanQuery. It is not recommended to change the rewrite mode for fuzzy queries.

At most, this query will match terms up to MAXIMUM_SUPPORTED_DISTANCE edits. Higher distances (especially with transpositions enabled), are generally not useful and will match a significant amount of the term dictionary. If you really want this, consider using an n-gram indexing technique (such as the SpellChecker in the suggest module) instead.

NOTE: terms of length 1 or 2 will sometimes not match because of how the scaled distance between two terms is computed. For a term to match, the edit distance between the terms must be less than the minimum length term (either the input term, or the candidate term). For example, FuzzyQuery on term "abcd" with maxEdits=2 will not match an indexed term "ab", and FuzzyQuery on term "a" with maxEdits=2 will not match an indexed term "abc".

Declaration

public const int DefaultMaxExpansions = 50

Field Value

Type	Description
int

DefaultMinSimilarity

Implements the fuzzy search query. The similarity measurement is based on the Damerau-Levenshtein (optimal string alignment) algorithm, though you can explicitly choose classic Levenshtein by passing false to the transpositions parameter.

this query uses MultiTermQuery.TopTermsScoringBooleanQueryRewrite as default. So terms will be collected and scored according to their edit distance. Only the top terms are used for building the BooleanQuery. It is not recommended to change the rewrite mode for fuzzy queries.

At most, this query will match terms up to MAXIMUM_SUPPORTED_DISTANCE edits. Higher distances (especially with transpositions enabled), are generally not useful and will match a significant amount of the term dictionary. If you really want this, consider using an n-gram indexing technique (such as the SpellChecker in the suggest module) instead.

NOTE: terms of length 1 or 2 will sometimes not match because of how the scaled distance between two terms is computed. For a term to match, the edit distance between the terms must be less than the minimum length term (either the input term, or the candidate term). For example, FuzzyQuery on term "abcd" with maxEdits=2 will not match an indexed term "ab", and FuzzyQuery on term "a" with maxEdits=2 will not match an indexed term "abc".

Declaration

[Obsolete("pass integer edit distances instead.")]
public const float DefaultMinSimilarity = 2

Field Value

Type	Description
float

DefaultPrefixLength

Implements the fuzzy search query. The similarity measurement is based on the Damerau-Levenshtein (optimal string alignment) algorithm, though you can explicitly choose classic Levenshtein by passing false to the transpositions parameter.

this query uses MultiTermQuery.TopTermsScoringBooleanQueryRewrite as default. So terms will be collected and scored according to their edit distance. Only the top terms are used for building the BooleanQuery. It is not recommended to change the rewrite mode for fuzzy queries.

At most, this query will match terms up to MAXIMUM_SUPPORTED_DISTANCE edits. Higher distances (especially with transpositions enabled), are generally not useful and will match a significant amount of the term dictionary. If you really want this, consider using an n-gram indexing technique (such as the SpellChecker in the suggest module) instead.

NOTE: terms of length 1 or 2 will sometimes not match because of how the scaled distance between two terms is computed. For a term to match, the edit distance between the terms must be less than the minimum length term (either the input term, or the candidate term). For example, FuzzyQuery on term "abcd" with maxEdits=2 will not match an indexed term "ab", and FuzzyQuery on term "a" with maxEdits=2 will not match an indexed term "abc".

Declaration

public const int DefaultPrefixLength = 0

Field Value

Type	Description
int

DefaultTranspositions

Implements the fuzzy search query. The similarity measurement is based on the Damerau-Levenshtein (optimal string alignment) algorithm, though you can explicitly choose classic Levenshtein by passing false to the transpositions parameter.

this query uses MultiTermQuery.TopTermsScoringBooleanQueryRewrite as default. So terms will be collected and scored according to their edit distance. Only the top terms are used for building the BooleanQuery. It is not recommended to change the rewrite mode for fuzzy queries.

At most, this query will match terms up to MAXIMUM_SUPPORTED_DISTANCE edits. Higher distances (especially with transpositions enabled), are generally not useful and will match a significant amount of the term dictionary. If you really want this, consider using an n-gram indexing technique (such as the SpellChecker in the suggest module) instead.

NOTE: terms of length 1 or 2 will sometimes not match because of how the scaled distance between two terms is computed. For a term to match, the edit distance between the terms must be less than the minimum length term (either the input term, or the candidate term). For example, FuzzyQuery on term "abcd" with maxEdits=2 will not match an indexed term "ab", and FuzzyQuery on term "a" with maxEdits=2 will not match an indexed term "abc".

Declaration

public const bool DefaultTranspositions = true

Field Value

Type	Description
bool

Properties

MaxEdits

Implements the fuzzy search query. The similarity measurement is based on the Damerau-Levenshtein (optimal string alignment) algorithm, though you can explicitly choose classic Levenshtein by passing false to the transpositions parameter.

this query uses MultiTermQuery.TopTermsScoringBooleanQueryRewrite as default. So terms will be collected and scored according to their edit distance. Only the top terms are used for building the BooleanQuery. It is not recommended to change the rewrite mode for fuzzy queries.

At most, this query will match terms up to MAXIMUM_SUPPORTED_DISTANCE edits. Higher distances (especially with transpositions enabled), are generally not useful and will match a significant amount of the term dictionary. If you really want this, consider using an n-gram indexing technique (such as the SpellChecker in the suggest module) instead.

NOTE: terms of length 1 or 2 will sometimes not match because of how the scaled distance between two terms is computed. For a term to match, the edit distance between the terms must be less than the minimum length term (either the input term, or the candidate term). For example, FuzzyQuery on term "abcd" with maxEdits=2 will not match an indexed term "ab", and FuzzyQuery on term "a" with maxEdits=2 will not match an indexed term "abc".

Declaration

public virtual int MaxEdits { get; }

Property Value

Type	Description
int	The maximum number of edit distances allowed for this query to match.

PrefixLength

Returns the non-fuzzy prefix length. This is the number of characters at the start of a term that must be identical (not fuzzy) to the query term if the query is to match that term.

Declaration

public virtual int PrefixLength { get; }

Property Value

Type	Description
int

Term

Returns the pattern term.

Declaration

public virtual Term Term { get; }

Property Value

Type	Description
Term

Transpositions

Returns true if transpositions should be treated as a primitive edit operation. If this is false, comparisons will implement the classic Levenshtein algorithm.

Declaration

public virtual bool Transpositions { get; }

Property Value

Type	Description
bool

Methods

Equals(object)

Determines whether the specified object is equal to the current object.

Declaration

public override bool Equals(object obj)

Parameters

Type	Name	Description
object	obj	The object to compare with the current object.

Returns

Type	Description
bool	true if the specified object is equal to the current object; otherwise, false.

Overrides

MultiTermQuery.Equals(object)

GetHashCode()

Serves as the default hash function.

Declaration

public override int GetHashCode()

Returns

Type	Description
int	A hash code for the current object.

Overrides

MultiTermQuery.GetHashCode()

GetTermsEnum(Terms, AttributeSource)

Construct the enumeration to be used, expanding the pattern term. this method should only be called if the field exists (ie, implementations can assume the field does exist). this method should not return null (should instead return EMPTY if no terms match). The TermsEnum must already be positioned to the first matching term. The given AttributeSource is passed by the MultiTermQuery.RewriteMethod to provide attributes, the rewrite method uses to inform about e.g. maximum competitive boosts. this is currently only used by TopTermsRewrite<Q>.

Declaration

protected override TermsEnum GetTermsEnum(Terms terms, AttributeSource atts)

Parameters

Type	Name	Description
Terms	terms
AttributeSource	atts

Returns

Type	Description
TermsEnum

Overrides

MultiTermQuery.GetTermsEnum(Terms, AttributeSource)

SingleToEdits(float, int)

Helper function to convert from deprecated "minimumSimilarity" fractions to raw edit distances.

NOTE: this was floatToEdits() in Lucene

Declaration

[Obsolete("pass integer edit distances instead.")]
public static int SingleToEdits(float minimumSimilarity, int termLen)

Parameters

Type	Name	Description
float	minimumSimilarity	Scaled similarity
int	termLen	Length (in unicode codepoints) of the term.

Returns

Type	Description
int	Equivalent number of maxEdits

ToString(string)

Prints a query to a string, with field assumed to be the default field and omitted.

Declaration

public override string ToString(string field)

Parameters

Type	Name	Description
string	field

Returns

Type	Description
string

Overrides

Query.ToString(string)