| Methods Summary |
|---|
| private static float | byteToFloat(byte b)
if (b == 0) // zero is a special case
return 0.0f;
int mantissa = b & 7;
int exponent = (b >> 3) & 31;
int bits = ((exponent+(63-15)) << 24) | (mantissa << 21);
return Float.intBitsToFloat(bits);
|
| public abstract float | coord(int overlap, int maxOverlap)Computes a score factor based on the fraction of all query terms that a
document contains. This value is multiplied into scores.
The presence of a large portion of the query terms indicates a better
match with the query, so implemenations of this method usually return
larger values when the ratio between these parameters is large and smaller
values when the ratio between them is small.
|
| public static float | decodeNorm(byte b)Decodes a normalization factor stored in an index.
for (int i = 0; i < 256; i++)
NORM_TABLE[i] = byteToFloat((byte)i);
return NORM_TABLE[b & 0xFF];
|
| public static byte | encodeNorm(float f)Encodes a normalization factor for storage in an index.
The encoding uses a five-bit exponent and three-bit mantissa, thus
representing values from around 7x10^9 to 2x10^-9 with about one
significant decimal digit of accuracy. Zero is also represented.
Negative numbers are rounded up to zero. Values too large to represent
are rounded down to the largest representable value. Positive values too
small to represent are rounded up to the smallest positive representable
value.
return floatToByte(f);
|
| private static byte | floatToByte(float f)
if (f < 0.0f) // round negatives up to zero
f = 0.0f;
if (f == 0.0f) // zero is a special case
return 0;
int bits = Float.floatToIntBits(f); // parse float into parts
int mantissa = (bits & 0xffffff) >> 21;
int exponent = (((bits >> 24) & 0x7f) - 63) + 15;
if (exponent > 31) { // overflow: use max value
exponent = 31;
mantissa = 7;
}
if (exponent < 0) { // underflow: use min value
exponent = 0;
mantissa = 1;
}
return (byte)((exponent << 3) | mantissa); // pack into a byte
|
| public static org.apache.lucene.search.Similarity | getDefault()Return the default Similarity implementation used by indexing and search
code.
This is initially an instance of {@link DefaultSimilarity}.
return Similarity.defaultImpl;
|
| public float | idf(org.apache.lucene.index.Term term, org.apache.lucene.search.Searcher searcher)Computes a score factor for a simple term.
The default implementation is:
return idf(searcher.docFreq(term), searcher.maxDoc());
Note that {@link Searcher#maxDoc()} is used instead of
{@link IndexReader#numDocs()} because it is proportional to
{@link Searcher#docFreq(Term)} , i.e., when one is inaccurate,
so is the other, and in the same direction.
return idf(searcher.docFreq(term), searcher.maxDoc());
|
| public float | idf(java.util.Collection terms, org.apache.lucene.search.Searcher searcher)Computes a score factor for a phrase.
The default implementation sums the {@link #idf(Term,Searcher)} factor
for each term in the phrase.
float idf = 0.0f;
Iterator i = terms.iterator();
while (i.hasNext()) {
idf += idf((Term)i.next(), searcher);
}
return idf;
|
| public abstract float | idf(int docFreq, int numDocs)Computes a score factor based on a term's document frequency (the number
of documents which contain the term). This value is multiplied by the
{@link #tf(int)} factor for each term in the query and these products are
then summed to form the initial score for a document.
Terms that occur in fewer documents are better indicators of topic, so
implemenations of this method usually return larger values for rare terms,
and smaller values for common terms.
|
| public abstract float | lengthNorm(java.lang.String fieldName, int numTokens)Computes the normalization value for a field given the total number of
terms contained in a field. These values, together with field boosts, are
stored in an index and multipled into scores for hits on each field by the
search code.
Matches in longer fields are less precise, so implemenations of this
method usually return smaller values when numTokens is large,
and larger values when numTokens is small.
That these values are computed under {@link
IndexWriter#addDocument(Document)} and stored then using
{#encodeNorm(float)}. Thus they have limited precision, and documents
must be re-indexed if this method is altered.
|
| public abstract float | queryNorm(float sumOfSquaredWeights)Computes the normalization value for a query given the sum of the squared
weights of each of the query terms. This value is then multipled into the
weight of each query term.
This does not affect ranking, but rather just attempts to make scores
from different queries comparable.
|
| public static void | setDefault(org.apache.lucene.search.Similarity similarity)Set the default Similarity implementation used by indexing and search
code.
Similarity.defaultImpl = similarity;
|
| public abstract float | sloppyFreq(int distance)Computes the amount of a sloppy phrase match, based on an edit distance.
This value is summed for each sloppy phrase match in a document to form
the frequency that is passed to {@link #tf(float)}.
A phrase match with a small edit distance to a document passage more
closely matches the document, so implementations of this method usually
return larger values when the edit distance is small and smaller values
when it is large.
|
| public abstract float | tf(float freq)Computes a score factor based on a term or phrase's frequency in a
document. This value is multiplied by the {@link #idf(Term, Searcher)}
factor for each term in the query and these products are then summed to
form the initial score for a document.
Terms and phrases repeated in a document indicate the topic of the
document, so implemenations of this method usually return larger values
when freq is large, and smaller values when freq
is small.
|
| public float | tf(int freq)Computes a score factor based on a term or phrase's frequency in a
document. This value is multiplied by the {@link #idf(Term, Searcher)}
factor for each term in the query and these products are then summed to
form the initial score for a document.
Terms and phrases repeated in a document indicate the topic of the
document, so implementations of this method usually return larger values
when freq is large, and smaller values when freq
is small.
The default implementation calls {@link #tf(float)}.
return tf((float)freq);
|
