Class BM25Similarity

BM25 Similarity. Introduced in Stephen E. Robertson, Steve Walker, Susan Jones, Micheline Hancock-Beaulieu, and Mike Gatford. Okapi at TREC-3. In Proceedings of the Third Text REtrieval Conference (TREC 1994). Gaithersburg, USA, November 1994.

This is a Lucene.NET EXPERIMENTAL API, use at your own risk
Inheritance
System.Object
Similarity
BM25Similarity
Inherited Members
Namespace: Lucene.Net.Search.Similarities
Assembly: Lucene.Net.dll
Syntax
public class BM25Similarity : Similarity

Constructors

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BM25Similarity()

BM25 with these default values:

  • k1 = 1.2,
  • b = 0.75.

Declaration
public BM25Similarity()
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BM25Similarity(Single, Single)

BM25 with the supplied parameter values.

Declaration
public BM25Similarity(float k1, float b)
Parameters
Type Name Description
System.Single k1

Controls non-linear term frequency normalization (saturation).

System.Single b

Controls to what degree document length normalizes tf values.

Properties

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B

Returns the b parameter

Declaration
public virtual float B { get; }
Property Value
Type Description
System.Single
See Also
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DiscountOverlaps

Gets or Sets 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.

Declaration
public virtual bool DiscountOverlaps { get; set; }
Property Value
Type Description
System.Boolean
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K1

Returns the k1 parameter

Declaration
public virtual float K1 { get; }
Property Value
Type Description
System.Single
See Also

Methods

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AvgFieldLength(CollectionStatistics)

The default implementation computes the average as sumTotalTermFreq / maxDoc, or returns 1 if the index does not store sumTotalTermFreq (Lucene 3.x indexes or any field that omits frequency information).

Declaration
protected virtual float AvgFieldLength(CollectionStatistics collectionStats)
Parameters
Type Name Description
CollectionStatistics collectionStats
Returns
Type Description
System.Single
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ComputeNorm(FieldInvertState)

Declaration
public override sealed long ComputeNorm(FieldInvertState state)
Parameters
Type Name Description
FieldInvertState state
Returns
Type Description
System.Int64
Overrides
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ComputeWeight(Single, CollectionStatistics, TermStatistics[])

Declaration
public override sealed Similarity.SimWeight ComputeWeight(float queryBoost, CollectionStatistics collectionStats, params TermStatistics[] termStats)
Parameters
Type Name Description
System.Single queryBoost
CollectionStatistics collectionStats
TermStatistics[] termStats
Returns
Type Description
Similarity.SimWeight
Overrides
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DecodeNormValue(Byte)

The default implementation returns 1 / f2 where f is Byte315ToSingle(Byte).

Declaration
protected virtual float DecodeNormValue(byte b)
Parameters
Type Name Description
System.Byte b
Returns
Type Description
System.Single
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EncodeNormValue(Single, Int32)

The default implementation encodes boost / sqrt(length) with SingleToByte315(Single). This is compatible with Lucene's default implementation. If you change this, then you should change DecodeNormValue(Byte) to match.

Declaration
protected virtual byte EncodeNormValue(float boost, int fieldLength)
Parameters
Type Name Description
System.Single boost
System.Int32 fieldLength
Returns
Type Description
System.Byte
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GetSimScorer(Similarity.SimWeight, AtomicReaderContext)

Declaration
public override sealed Similarity.SimScorer GetSimScorer(Similarity.SimWeight stats, AtomicReaderContext context)
Parameters
Type Name Description
Similarity.SimWeight stats
AtomicReaderContext context
Returns
Type Description
Similarity.SimScorer
Overrides
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Idf(Int64, Int64)

Implemented as log(1 + (numDocs - docFreq + 0.5)/(docFreq + 0.5)).

Declaration
protected virtual float Idf(long docFreq, long numDocs)
Parameters
Type Name Description
System.Int64 docFreq
System.Int64 numDocs
Returns
Type Description
System.Single
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IdfExplain(CollectionStatistics, TermStatistics)

Computes a score factor for a simple term and returns an explanation for that score factor.

The default implementation uses:

    Idf(docFreq, searcher.MaxDoc);

Note that MaxDoc is used instead of NumDocs because also DocFreq is used, and when the latter is inaccurate, so is MaxDoc, and in the same direction. In addition, MaxDoc is more efficient to compute

Declaration
public virtual Explanation IdfExplain(CollectionStatistics collectionStats, TermStatistics termStats)
Parameters
Type Name Description
CollectionStatistics collectionStats

collection-level statistics

TermStatistics termStats

term-level statistics for the term

Returns
Type Description
Explanation

an Explanation object that includes both an idf score factor and an explanation for the term.

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IdfExplain(CollectionStatistics, TermStatistics[])

Computes a score factor for a phrase.

The default implementation sums the idf factor for each term in the phrase.

Declaration
public virtual Explanation IdfExplain(CollectionStatistics collectionStats, TermStatistics[] termStats)
Parameters
Type Name Description
CollectionStatistics collectionStats

collection-level statistics

TermStatistics[] termStats

term-level statistics for the terms in the phrase

Returns
Type Description
Explanation

an Explanation object that includes both an idf score factor for the phrase and an explanation for each term.

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ScorePayload(Int32, Int32, Int32, BytesRef)

The default implementation returns 1

Declaration
protected virtual float ScorePayload(int doc, int start, int end, BytesRef payload)
Parameters
Type Name Description
System.Int32 doc
System.Int32 start
System.Int32 end
BytesRef payload
Returns
Type Description
System.Single
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SloppyFreq(Int32)

Implemented as 1 / (distance + 1).

Declaration
protected virtual float SloppyFreq(int distance)
Parameters
Type Name Description
System.Int32 distance
Returns
Type Description
System.Single
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ToString()

Declaration
public override string ToString()
Returns
Type Description
System.String