public abstract class Similarity extends Object
| Constructor and Description |
|---|
Similarity() |
| Modifier and Type | Method and Description |
|---|---|
abstract float |
coord(int overlap,
int maxOverlap)
Computes a score factor based on the fraction of all query terms that a
document contains.
|
static float |
decodeNorm(byte b)
Decodes a normalization factor stored in an index.
|
static byte |
encodeNorm(float f)
Encodes a normalization factor for storage in an index.
|
static Similarity |
getDefault()
Return the default Similarity implementation used by indexing and search
code.
|
float |
idf(Collection terms,
Searcher searcher)
Computes a score factor for a phrase.
|
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).
|
float |
idf(Term term,
Searcher searcher)
Computes a score factor for a simple term.
|
abstract float |
lengthNorm(String fieldName,
int numTokens)
Computes the normalization value for a field given the total number of
terms contained in a field.
|
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.
|
static void |
setDefault(Similarity similarity)
Set the default Similarity implementation used by indexing and search
code.
|
abstract float |
sloppyFreq(int distance)
Computes the amount of a sloppy phrase match, based on an edit distance.
|
abstract float |
tf(float freq)
Computes a score factor based on a term or phrase's frequency in a
document.
|
float |
tf(int freq)
Computes a score factor based on a term or phrase's frequency in a
document.
|
public static void setDefault(Similarity similarity)
public static Similarity getDefault()
This is initially an instance of DefaultSimilarity.
public static float decodeNorm(byte b)
encodeNorm(float)public abstract float lengthNorm(String fieldName, int numTokens)
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 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.
fieldName - the name of the fieldnumTokens - the total number of tokens contained in fields named
fieldName of doc.Field.setBoost(float)public abstract float queryNorm(float sumOfSquaredWeights)
This does not affect ranking, but rather just attempts to make scores from different queries comparable.
sumOfSquaredWeights - the sum of the squares of query term weightspublic static byte encodeNorm(float f)
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.
Field.setBoost(float)public float tf(int freq)
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 tf(float).
freq - the frequency of a term within a documentpublic abstract float sloppyFreq(int distance)
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.
distance - the edit distance of this sloppy phrase matchPhraseQuery.setSlop(int)public abstract float tf(float freq)
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.
freq - the frequency of a term within a documentpublic float idf(Term term, Searcher searcher) throws IOException
The default implementation is:
return idf(searcher.docFreq(term), searcher.maxDoc());Note that
Searchable.maxDoc() is used instead of
IndexReader.numDocs() because it is proportional to
Searchable.docFreq(Term) , i.e., when one is inaccurate,
so is the other, and in the same direction.term - the term in questionsearcher - the document collection being searchedIOExceptionpublic float idf(Collection terms, Searcher searcher) throws IOException
The default implementation sums the idf(Term,Searcher) factor
for each term in the phrase.
terms - the terms in the phrasesearcher - the document collection being searchedIOExceptionpublic abstract float idf(int docFreq,
int numDocs)
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.
docFreq - the number of documents which contain the termnumDocs - the total number of documents in the collectionpublic abstract float coord(int overlap,
int maxOverlap)
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.
overlap - the number of query terms matched in the documentmaxOverlap - the total number of terms in the queryCopyright © 2024 GATE. All rights reserved.