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BM25Similarity Class

  • Reference

Definition

Namespace:
Azure.Search.Documents.Indexes.Models
Assembly:
Azure.Search.Documents.dll
Package:
Azure.Search.Documents v11.6.0
Package:
Azure.Search.Documents v11.7.0-beta.1
Source:
BM25Similarity.cs
Source:
BM25Similarity.cs

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).

public class BM25Similarity : Azure.Search.Documents.Indexes.Models.SimilarityAlgorithm
type BM25Similarity = class
    inherit SimilarityAlgorithm
Public Class BM25Similarity
Inherits SimilarityAlgorithm
Inheritance
Object
SimilarityAlgorithm
BM25Similarity

Constructors

BM25Similarity()

Initializes a new instance of 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.
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.

Applies to