Class SimilarityBase

A subclass of Similarity that provides a simplified API for its descendants. Subclasses are only required to implement the Score(BasicStats, float, float) and ToString() methods. Implementing Explain(Explanation, BasicStats, int, float, float) is optional, inasmuch as SimilarityBase already provides a basic explanation of the score and the term frequency. However, implementers of a subclass are encouraged to include as much detail about the scoring method as possible.

Note: multi-word queries such as phrase queries are scored in a different way than Lucene's default ranking algorithm: whereas it "fakes" an IDF value for the phrase as a whole (since it does not know it), this class instead scores phrases as a summation of the individual term scores.

Note

This API is experimental and might change in incompatible ways in the next release.

Inheritance

object

Similarity

SimilarityBase

DFRSimilarity

IBSimilarity

LMSimilarity

Inherited Members

Similarity.Coord(int, int)

Similarity.QueryNorm(float)

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

Namespace: Lucene.Net.Search.Similarities

Assembly: Lucene.Net.dll

Syntax

public abstract class SimilarityBase : Similarity

Constructors

SimilarityBase()

Sole constructor. (For invocation by subclass constructors, typically implicit.)

Declaration

protected SimilarityBase()

Properties

DiscountOverlaps

Determines whether overlap tokens (Tokens with 0 position increment) are ignored when computing norm. By default this is true, meaning overlap tokens do not count when computing norms.

Note

This API is experimental and might change in incompatible ways in the next release.

Declaration

public virtual bool DiscountOverlaps { get; set; }

Property Value

Type	Description
bool

See Also

ComputeNorm(FieldInvertState)

Methods

ComputeNorm(FieldInvertState)

Encodes the document length in the same way as TFIDFSimilarity.

Declaration

public override long ComputeNorm(FieldInvertState state)

Parameters

Type	Name	Description
FieldInvertState	state

Returns

Type	Description
long

Overrides

Similarity.ComputeNorm(FieldInvertState)

ComputeWeight(float, CollectionStatistics, params TermStatistics[])

Compute any collection-level weight (e.g. IDF, average document length, etc) needed for scoring a query.

Declaration

public override sealed Similarity.SimWeight ComputeWeight(float queryBoost, CollectionStatistics collectionStats, params TermStatistics[] termStats)

Parameters

Type	Name	Description
float	queryBoost	the query-time boost.
CollectionStatistics	collectionStats	collection-level statistics, such as the number of tokens in the collection.
TermStatistics[]	termStats	term-level statistics, such as the document frequency of a term across the collection.

Returns

Type	Description
Similarity.SimWeight	Similarity.SimWeight object with the information this Similarity needs to score a query.

Overrides

Similarity.ComputeWeight(float, CollectionStatistics, params TermStatistics[])

DecodeNormValue(byte)

Decodes a normalization factor (document length) stored in an index.

Declaration

protected virtual float DecodeNormValue(byte norm)

Parameters

Type	Name	Description
byte	norm

Returns

Type	Description
float

EncodeNormValue(float, float)

Encodes the length to a byte via SmallSingle.

Declaration

protected virtual byte EncodeNormValue(float boost, float length)

Parameters

Type	Name	Description
float	boost
float	length

Returns

Type	Description
byte

Explain(Explanation, BasicStats, int, float, float)

Subclasses should implement this method to explain the score. expl already contains the score, the name of the class and the doc id, as well as the term frequency and its explanation; subclasses can add additional clauses to explain details of their scoring formulae.

The default implementation does nothing.

Declaration

protected virtual void Explain(Explanation expl, BasicStats stats, int doc, float freq, float docLen)

Parameters

Type	Name	Description
Explanation	expl	the explanation to extend with details.
BasicStats	stats	the corpus level statistics.
int	doc	the document id.
float	freq	the term frequency.
float	docLen	the document length.

Explain(BasicStats, int, Explanation, float)

Explains the score. The implementation here provides a basic explanation in the format Score(name-of-similarity, doc=doc-id, freq=term-frequency), computed from:, and attaches the score (computed via the Score(BasicStats, float, float) method) and the explanation for the term frequency. Subclasses content with this format may add additional details in Explain(Explanation, BasicStats, int, float, float).

Declaration

public virtual Explanation Explain(BasicStats stats, int doc, Explanation freq, float docLen)

Parameters

Type	Name	Description
BasicStats	stats	the corpus level statistics.
int	doc	the document id.
Explanation	freq	the term frequency and its explanation.
float	docLen	the document length.

Returns

Type	Description
Explanation	the explanation.

FillBasicStats(BasicStats, CollectionStatistics, TermStatistics)

Fills all member fields defined in BasicStats in stats. Subclasses can override this method to fill additional stats.

Declaration

protected virtual void FillBasicStats(BasicStats stats, CollectionStatistics collectionStats, TermStatistics termStats)

Parameters

Type	Name	Description
BasicStats	stats
CollectionStatistics	collectionStats
TermStatistics	termStats

GetSimScorer(SimWeight, AtomicReaderContext)

Creates a new Similarity.SimScorer to score matching documents from a segment of the inverted index.

Declaration

public override Similarity.SimScorer GetSimScorer(Similarity.SimWeight stats, AtomicReaderContext context)

Parameters

Type	Name	Description
Similarity.SimWeight	stats
AtomicReaderContext	context	segment of the inverted index to be scored.

Returns

Type	Description
Similarity.SimScorer	Sloppy Similarity.SimScorer for scoring documents across context

Overrides

Similarity.GetSimScorer(Similarity.SimWeight, AtomicReaderContext)

Exceptions

Type	Condition
IOException	if there is a low-level I/O error

Log2(double)

Returns the base two logarithm of x.

Declaration

public static double Log2(double x)

Parameters

Type	Name	Description
double	x

Returns

Type	Description
double

NewStats(string, float)

Factory method to return a custom stats object

Declaration

protected virtual BasicStats NewStats(string field, float queryBoost)

Parameters

Type	Name	Description
string	field
float	queryBoost

Returns

Type	Description
BasicStats

Score(BasicStats, float, float)

Scores the document doc.

Subclasses must apply their scoring formula in this class.

Declaration

public abstract float Score(BasicStats stats, float freq, float docLen)

Parameters

Type	Name	Description
BasicStats	stats	the corpus level statistics.
float	freq	the term frequency.
float	docLen	the document length.

Returns

Type	Description
float	the score.

ToString()

Subclasses must override this method to return the name of the Similarity and preferably the values of parameters (if any) as well.

Declaration

public override abstract string ToString()

Returns

Type	Description
string

Overrides

object.ToString()