Lucene Similarity Scoring Formula

score(q,d) = coord(q,d)·queryNorm(q)·∑(tf(t in d)·idf(t)^2·t.getBoost()·norm(t,d)) (∑: t in q)

d:document
t:term
q:query

coor(q, d):
  public float coord(int overlap, int maxOverlap)
Implemented as overlap / maxOverlap.
overlap - the number of query terms matched in the document
maxOverlap - the total number of terms in the query

queryNorm(q):
  public float queryNorm(float sumOfSquaredWeights)
Implemented as 1/sqrt(sumOfSquaredWeights).
sumOfSquaredWeights - the sum of the squares of query term weights
sumOfSquaredWeights = q.getBoost()^2·∑(idf(t)·t.getBoost())^2   (∑:t in q)

idf(t):
  public float idf(long docFreq, long numDocs)
Implemented as log(numDocs/(docFreq+1)) + 1.
docFreq - the number of documents which contain the term
numDocs - the total number of documents in the collection(all the indices)

tf(t ind d):
  public float tf(float freq)
Implemented as sqrt(freq).
freq - the frequency of a term within a document

boost(t.field in d):
  public void setBoost(float b)
Sets the boost for this query clause to b.
  public float getBoost()
The boost is 1.0 by default.

norm(t, d):
norm(t,d) = lengthNorm·∏f.boost()  (∏:field f in d named as t)
  If the document has multiple fields with the same name, all their boosts are multiplied together.
lengthNorm = 1.0 / Math.sqrt(numTerms)
lengthNorm-computed when the document is added to the index in accordance with the number of tokens of this field in the document, so that shorter fields contribute more to the score. LengthNorm is computed by the Similarity class in effect at indexing.
Shorter fields (fewer tokens) get a bigger boost from this factor.
numTerms is the number of terms within a field, 
numTerms is FieldInvertState.getLength() if setDiscountOverlaps(boolean) is false, else it's FieldInvertState.getLength() - FieldInvertState.getNumOverlap().
FieldInvertState.getLength(): Get total number of terms in this field.