Package org.apache.lucene.search.uhighlight

# Class PassageScorer

java.lang.Object
org.apache.lucene.search.uhighlight.PassageScorer

public class PassageScorer extends Object
Ranks passages found by `UnifiedHighlighter`.

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

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

- ## Constructor Summary

  Constructors
  Constructor
  Description
  `PassageScorer()`
  Creates PassageScorer with these default values: `k1 = 1.2`, `b = 0.75`.
  `PassageScorer(float k1, float b, float pivot)`
  Creates PassageScorer with specified scoring parameters

- ## Method Summary

  Modifier and Type
  Method
  Description
  `float`
  `norm(int passageStart)`
  Normalize a passage according to its position in the document.
  `float`
  `score(Passage passage, int contentLength)`
  `float`
  `tf(int freq, int passageLen)`
  Computes term weight, given the frequency within the passage and the passage's length.
  `float`
  `weight(int contentLength, int totalTermFreq)`
  Computes term importance, given its in-document statistics.

  ### Methods inherited from class java.lang.Object

  `clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

- ## Constructor Details

  - ### PassageScorer

    public PassageScorer()
    Creates PassageScorer with these default values:
    - `k1 = 1.2`,
    - `b = 0.75`.
    - `pivot = 87`

  - ### PassageScorer

    public PassageScorer(float k1, float b, float pivot)
    Creates PassageScorer with specified scoring parameters
    Parameters:
      `k1` - Controls non-linear term frequency normalization (saturation).
      `b` - Controls to what degree passage length normalizes tf values.
      `pivot` - Pivot value for length normalization (some rough idea of average sentence length in characters).

- ## Method Details

  - ### weight

    public float weight(int contentLength, int totalTermFreq)
    Computes term importance, given its in-document statistics.
    Parameters:
      `contentLength` - length of document in characters
      `totalTermFreq` - number of time term occurs in document
    Returns:
      term importance

  - ### tf

    public float tf(int freq, int passageLen)
    Computes term weight, given the frequency within the passage and the passage's length.
    Parameters:
      `freq` - number of occurrences of within this passage
      `passageLen` - length of the passage in characters.
    Returns:
      term weight

  - ### norm

    public float norm(int passageStart)
    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)`

    Parameters:
      `passageStart` - start offset of the passage
    Returns:
      a boost value multiplied into the passage's core.

  - ### score

    public float score(Passage passage, int contentLength)