org.apache.lucene.search
Class SimilarityDelegator
- Serializable
public class SimilarityDelegator
Expert: Delegating scoring implementation. Useful in
Query.getSimilarity(Searcher)
implementations, to override only certain
methods of a Searcher's Similiarty implementation..
float | coord(int overlap, int maxOverlap) - Computes a score factor based on the fraction of all query terms that a
document contains.
|
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 | lengthNorm(String fieldName, int numTerms) - Computes the normalization value for a field given the total number of
terms contained in a field.
|
float | queryNorm(float sumOfSquaredWeights) - Computes the normalization value for a query given the sum of the squared
weights of each of the query terms.
|
float | sloppyFreq(int distance) - Computes the amount of a sloppy phrase match, based on an edit distance.
|
float | tf(float freq) - Computes a score factor based on a term or phrase's frequency in a
document.
|
coord , decodeNorm , encodeNorm , getDefault , getNormDecoder , idf , idf , idf , lengthNorm , queryNorm , setDefault , sloppyFreq , tf , tf |
SimilarityDelegator
public SimilarityDelegator(Similarity delegee)
Construct a
Similarity
that delegates all methods to another.
delegee
- the Similarity implementation to delegate to
coord
public 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 implementations 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.
- coord in interface Similarity
overlap
- the number of query terms matched in the documentmaxOverlap
- the total number of terms in the query
- a score factor based on term overlap with the query
idf
public 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
Similarity.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
implementations of this method usually return larger values for rare terms,
and smaller values for common terms.
- idf in interface Similarity
docFreq
- the number of documents which contain the termnumDocs
- the total number of documents in the collection
- a score factor based on the term's document frequency
lengthNorm
public float lengthNorm(String fieldName,
int numTerms)
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 implementations 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
Similarity.encodeNorm(float)
. Thus they have limited precision, and documents
must be re-indexed if this method is altered.
- lengthNorm in interface Similarity
fieldName
- the name of the field
- a normalization factor for hits on this field of this document
queryNorm
public 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.
- queryNorm in interface Similarity
sumOfSquaredWeights
- the sum of the squares of query term weights
- a normalization factor for query weights
sloppyFreq
public 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
Similarity.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.
- sloppyFreq in interface Similarity
distance
- the edit distance of this sloppy phrase match
- the frequency increment for this match
tf
public 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
Similarity.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.
- tf in interface Similarity
freq
- the frequency of a term within a document
- a score factor based on a term's within-document frequency
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