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API Documentation

lucene::search::Similarity Class Reference

Expert: Scoring API. More...

#include <Similarity.h>

Inheritance diagram for lucene::search::Similarity:

lucene::search::DefaultSimilarity

Public Member Functions

virtual ~Similarity ()
float_t idf (lucene::util::CLVector< lucene::index::Term * > *terms, Searcher *searcher)
 Computes a score factor for a phrase.
float_t idf (lucene::index::Term *term, Searcher *searcher)
 Computes a score factor for a simple term.
float_t tf (int32_t freq)
 Computes a score factor based on a term or phrase's frequency in a document.
virtual float_t lengthNorm (const TCHAR *fieldName, int32_t numTokens)=0
 Computes the normalization value for a field given the total number of terms contained in a field.
virtual float_t queryNorm (float_t sumOfSquaredWeights)=0
 Computes the normalization value for a query given the sum of the squared weights of each of the query terms.
virtual float_t sloppyFreq (int32_t distance)=0
 Computes the amount of a sloppy phrase match, based on an edit distance.
virtual float_t tf (float_t freq)=0
 Computes a score factor based on a term or phrase's frequency in a document.
virtual float_t idf (int32_t docFreq, int32_t numDocs)=0
 Computes a score factor based on a term's document frequency (the number of documents which contain the term).
virtual float_t coord (int32_t overlap, int32_t maxOverlap)=0
 Computes a score factor based on the fraction of all query terms that a document contains.

Static Public Member Functions

static void setDefault (Similarity *similarity)
 Set the default Similarity implementation used by indexing and search code.
static Similarity * getDefault ()
 Return the default Similarity implementation used by indexing and search code.
static uint8_t encodeNorm (float_t f)
 Encodes a normalization factor for storage in an index.
static float_t decodeNorm (uint8_t b)
 Decodes a normalization factor stored in an index.
static uint8_t floatToByte (float_t f)
static float_t byteToFloat (uint8_t b)

Detailed Description

Expert: Scoring API.

Subclasses implement search scoring.

The score of query q for document d is defined in terms of these methods as follows:

score(q,d) =
<big><big><big><big><big></big></big></big></big></big> tf(t in d) * idf(t) * getBoost(t.field in d) * lengthNorm(t.field in d)  * coord(q,d) * queryNorm(q)
t in q

See also:
setDefault(Similarity)

IndexWriter::setSimilarity(Similarity)

Searcher::setSimilarity(Similarity)

Constructor & Destructor Documentation

virtual lucene::search::Similarity::~Similarity (  )  [virtual]

Member Function Documentation

static void lucene::search::Similarity::setDefault ( Similarity *  similarity  )  [static]

Set the default Similarity implementation used by indexing and search code.

See also:
Searcher::setSimilarity(Similarity)

IndexWriter::setSimilarity(Similarity)

static Similarity* lucene::search::Similarity::getDefault (  )  [static]

Return the default Similarity implementation used by indexing and search code.

This is initially an instance of DefaultSimilarity.

See also:
Searcher::setSimilarity(Similarity)

IndexWriter::setSimilarity(Similarity)

static uint8_t lucene::search::Similarity::encodeNorm ( float_t  f  )  [static]

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.

See also:
Field::setBoost(float_t)

static float_t lucene::search::Similarity::decodeNorm ( uint8_t  b  )  [static]

Decodes a normalization factor stored in an index.

See also:
encodeNorm(float_t)

static uint8_t lucene::search::Similarity::floatToByte ( float_t  f  )  [static]

static float_t lucene::search::Similarity::byteToFloat ( uint8_t  b  )  [static]

float_t lucene::search::Similarity::idf ( lucene::util::CLVector< lucene::index::Term * > *  terms,
Searcher *  searcher 
)

Computes a score factor for a phrase.

The default implementation sums the idf(Term,Searcher) factor for each term in the phrase.

Parameters:
terms the terms in the phrase
searcher the document collection being searched
Returns:
a score factor for the phrase

float_t lucene::search::Similarity::idf ( lucene::index::Term *  term,
Searcher *  searcher 
)

Computes a score factor for a simple term.

The default implementation is:

   return idf(searcher.docFreq(term), searcher.maxDoc());

Note that Searcher#maxDoc() is used instead of IndexReader#numDocs() because it is proportional to Searcher#docFreq(Term) , i.e., when one is inaccurate, so is the other, and in the same direction.

Parameters:
term the term in question
searcher the document collection being searched
Returns:
a score factor for the term

float_t lucene::search::Similarity::tf ( int32_t  freq  )  [inline]

Computes a score factor based on a term or phrase's frequency in a document.

This value is multiplied by the 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_t).

Parameters:
freq the frequency of a term within a document
Returns:
a score factor based on a term's within-document frequency

virtual float_t lucene::search::Similarity::lengthNorm ( const TCHAR *  fieldName,
int32_t  numTokens 
) [pure virtual]

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 IndexWriter#addDocument(Document) and stored then using {encodeNorm(float_t)}. Thus they have limited precision, and documents must be re-indexed if this method is altered.

Parameters:
fieldName the name of the field
numTokens 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_t)

Implemented in lucene::search::DefaultSimilarity.

virtual float_t lucene::search::Similarity::queryNorm ( float_t  sumOfSquaredWeights  )  [pure virtual]

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.

Parameters:
sumOfSquaredWeights the sum of the squares of query term weights
Returns:
a normalization factor for query weights

Implemented in lucene::search::DefaultSimilarity.

virtual float_t lucene::search::Similarity::sloppyFreq ( int32_t  distance  )  [pure virtual]

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 tf(float_t).

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.

See also:
PhraseQuery::setSlop(int32_t)
Parameters:
distance the edit distance of this sloppy phrase match
Returns:
the frequency increment for this match

Implemented in lucene::search::DefaultSimilarity.

virtual float_t lucene::search::Similarity::tf ( float_t  freq  )  [pure virtual]

Computes a score factor based on a term or phrase's frequency in a document.

This value is multiplied by the 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.

Parameters:
freq the frequency of a term within a document
Returns:
a score factor based on a term's within-document frequency

Implemented in lucene::search::DefaultSimilarity.

virtual float_t lucene::search::Similarity::idf ( int32_t  docFreq,
int32_t  numDocs 
) [pure virtual]

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 tf(int32_t) 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.

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

Implemented in lucene::search::DefaultSimilarity.

virtual float_t lucene::search::Similarity::coord ( int32_t  overlap,
int32_t  maxOverlap 
) [pure virtual]

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.

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

Implemented in lucene::search::DefaultSimilarity.

The documentation for this class was generated from the following file:

clucene.sourceforge.net