Class PassageScorer

Ranks passages found by ICUPostingsHighlighter.

Each passage is scored as a miniature document within the document. The final score is computed as norm * ∑ (weight * tf). The default implementation is norm * BM25.

Note

This API is experimental and might change in incompatible ways in the next release.

Inheritance

object

PassageScorer

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Namespace: Lucene.Net.Search.PostingsHighlight

Assembly: Lucene.Net.ICU.dll

Syntax

public class PassageScorer

Constructors

PassageScorer()

Creates PassageScorer with these default values:

• k1 = 1.2
• b = 0.75
• pivot = 87

Declaration

public PassageScorer()

PassageScorer(float, float, float)

Creates PassageScorer with specified scoring parameters

Declaration

public PassageScorer(float k1, float b, float pivot)

Parameters

Type	Name	Description
float	k1	Controls non-linear term frequency normalization (saturation).
float	b	Controls to what degree passage length normalizes tf values.
float	pivot	Pivot value for length normalization (some rough idea of average sentence length in characters).

Methods

Norm(int)

Normalize a passage according to its position in the document.

Typically passages towards the beginning of the document are more useful for summarizing the contents.

The default implementation is 1 + 1/log(pivot + passageStart)

Declaration

public virtual float Norm(int passageStart)

Parameters

Type	Name	Description
int	passageStart	start offset of the passage

Returns

Type	Description
float	a boost value multiplied into the passage's core.

Tf(int, int)

Computes term weight, given the frequency within the passage and the passage's length.

Declaration

public virtual float Tf(int freq, int passageLen)

Parameters

Type	Name	Description
int	freq	number of occurrences of within this passage
int	passageLen	length of the passage in characters.

Returns

Type	Description
float	term weight

Weight(int, int)

Computes term importance, given its in-document statistics.

Declaration

public virtual float Weight(int contentLength, int totalTermFreq)

Parameters

Type	Name	Description
int	contentLength	length of document in characters
int	totalTermFreq	number of time term occurs in document

Returns

Type	Description
float	term importance