BM25Similarity Class
Definition
Important
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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.SimilarityAlgorithmtype BM25Similarity = class
inherit SimilarityAlgorithmPublic Class BM25Similarity
Inherits SimilarityAlgorithm- Inheritance
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. |
