Class BM25Similarity
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).
Namespace: System.Dynamic.ExpandoObject
Assembly: Azure.Search.Documents.dll
Syntax
public class BM25Similarity : Azure.Search.Documents.Indexes.Models.SimilarityAlgorithmConstructors
BM25Similarity()
Initializes a new instance of BM25Similarity.
Declaration
public BM25Similarity ();Properties
B
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.
Declaration
public Nullable<double> B { get; set; }Property Value
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System.Nullable<System.Double>
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K1
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.
Declaration
public Nullable<double> K1 { get; set; }Property Value
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System.Nullable<System.Double>
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