Class BM25SimilarityAlgorithm
- java.lang.Object
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- com.azure.search.documents.indexes.models.SimilarityAlgorithm
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- com.azure.search.documents.indexes.models.BM25SimilarityAlgorithm
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public final class BM25SimilarityAlgorithm extends SimilarityAlgorithm
Ranking function based on the Okapi BM25 similarity algorithm. BM25 is a TF-IDF-like algorithm that includes length normalization (controlled by the 'b' parameter) as well as term frequency saturation (controlled by the 'k1' parameter).
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Constructor Summary
Constructors Constructor Description BM25SimilarityAlgorithm()
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description Double
getB()
Get the b property: This property controls how the length of a document affects the relevance score.Double
getK1()
Get the k1 property: This property controls the scaling function between the term frequency of each matching terms and the final relevance score of a document-query pair.BM25SimilarityAlgorithm
setB(Double b)
Set the b property: This property controls how the length of a document affects the relevance score.BM25SimilarityAlgorithm
setK1(Double k1)
Set the k1 property: This property controls the scaling function between the term frequency of each matching terms and the final relevance score of a document-query pair.
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Method Detail
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getK1
public Double getK1()
Get the k1 property: This property controls the scaling function between the term frequency of each matching terms and the final relevance score of a document-query pair. By default, a value of 1.2 is used. A value of 0.0 means the score does not scale with an increase in term frequency.- Returns:
- the k1 value.
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setK1
public BM25SimilarityAlgorithm setK1(Double k1)
Set the k1 property: This property controls the scaling function between the term frequency of each matching terms and the final relevance score of a document-query pair. By default, a value of 1.2 is used. A value of 0.0 means the score does not scale with an increase in term frequency.- Parameters:
k1
- the k1 value to set.- Returns:
- the BM25SimilarityAlgorithm object itself.
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getB
public Double getB()
Get the b property: This property controls how the length of a document affects the relevance score. By default, a value of 0.75 is used. A value of 0.0 means no length normalization is applied, while a value of 1.0 means the score is fully normalized by the length of the document.- Returns:
- the b value.
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setB
public BM25SimilarityAlgorithm setB(Double b)
Set the b property: This property controls how the length of a document affects the relevance score. By default, a value of 0.75 is used. A value of 0.0 means no length normalization is applied, while a value of 1.0 means the score is fully normalized by the length of the document.- Parameters:
b
- the b value to set.- Returns:
- the BM25SimilarityAlgorithm object itself.
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