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## org.apache.lucene.search
Class DefaultSimilarity

    java.lang.Object
      org.apache.lucene.search.Similarity
          org.apache.lucene.search.DefaultSimilarity

public class DefaultSimilarity
extends Similarity

Expert: Default scoring implementation.

Constructor Summary
`DefaultSimilarity()`

Method Summary
`float` | `coord(int overlap, int maxOverlap)` Implemented as `overlap / maxOverlap`.
`float` | `idf(int docFreq, int numDocs)` Implemented as `log(numDocs/(docFreq+1)) + 1`.
`float` | `lengthNorm(String fieldName, int numTerms)` Implemented as `1/sqrt(numTerms)`.
`float` | `queryNorm(float sumOfSquaredWeights)` Implemented as `1/sqrt(sumOfSquaredWeights)`.
`float` | `sloppyFreq(int distance)` Implemented as `1 / (distance + 1)`.
`float` | `tf(float freq)` Implemented as `sqrt(freq)`.

Methods inherited from class org.apache.lucene.search.Similarity
`decodeNorm, encodeNorm, getDefault, idf, idf, setDefault, tf`

Methods inherited from class java.lang.Object
`clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

Constructor Detail

### DefaultSimilarity

    public DefaultSimilarity()

Method Detail

### lengthNorm

    public float lengthNorm(String fieldName,
                            int numTerms)

  Implemented as `1/sqrt(numTerms)`.

  Specified by:
    `lengthNorm` in class `Similarity`
  Parameters:
    `fieldName` - the name of the field
    `numTerms` - the total number of tokens contained in fields named fieldName of doc.
  Returns:
    a normalization factor for hits on this field of this document
  See Also:
    `Field.setBoost(float)`

### queryNorm

    public float queryNorm(float sumOfSquaredWeights)

  Implemented as `1/sqrt(sumOfSquaredWeights)`.

  Specified by:
    `queryNorm` in class `Similarity`
  Parameters:
    `sumOfSquaredWeights` - the sum of the squares of query term weights
  Returns:
    a normalization factor for query weights

### tf

    public float tf(float freq)

  Implemented as `sqrt(freq)`.

  Specified by:
    `tf` in class `Similarity`
  Parameters:
    `freq` - the frequency of a term within a document
  Returns:
    a score factor based on a term's within-document frequency

### sloppyFreq

    public float sloppyFreq(int distance)

  Implemented as `1 / (distance + 1)`.

  Specified by:
    `sloppyFreq` in class `Similarity`
  Parameters:
    `distance` - the edit distance of this sloppy phrase match
  Returns:
    the frequency increment for this match
  See Also:
    `PhraseQuery.setSlop(int)`

### idf

    public float idf(int docFreq,
                     int numDocs)

  Implemented as `log(numDocs/(docFreq+1)) + 1`.

  Specified by:
    `idf` in class `Similarity`
  Parameters:
    `docFreq` - the number of documents which contain the term
    `numDocs` - the total number of documents in the collection
  Returns:
    a score factor based on the term's document frequency

### coord

    public float coord(int overlap,
                       int maxOverlap)

  Implemented as `overlap / maxOverlap`.

  Specified by:
    `coord` in class `Similarity`
  Parameters:
    `overlap` - the number of query terms matched in the document
    `maxOverlap` - the total number of terms in the query
  Returns:
    a score factor based on term overlap with the query

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