Expert: Scoring API. Subclasses implement search scoring. More...

Inherited by Lucene.Net.Search.DefaultSimilarity, and Lucene.Net.Search.SimilarityDelegator.

Public Member Functions
virtual float	ComputeNorm (System.String field, FieldInvertState state)
	Compute the normalization value for a field, given the accumulated state of term processing for this field (see FieldInvertState).

abstract float	LengthNorm (System.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.

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.

virtual 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 Idf(int, int) factor for each term in the query and these products are then summed to form the initial score for a document.

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 Tf(float).

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 Idf(int, int) factor for each term in the query and these products are then summed to form the initial score for a document.

virtual IDFExplanation	IdfExplain (Term term, Searcher searcher)
	Computes a score factor for a simple term and returns an explanation for that score factor.

virtual IDFExplanation	IdfExplain (ICollection< Term > 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). This value is multiplied by the Tf(int) factor for each term in the query and these products are then summed to form the initial score for a document.

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.

virtual float	ScorePayload (int docId, System.String fieldName, int start, int end, byte[] payload, int offset, int length)
	Calculate a scoring factor based on the data in the payload. Overriding implementations are responsible for interpreting what is in the payload. Lucene makes no assumptions about what is in the byte array. The default implementation returns 1.

Static Public Member Functions
static float	DecodeNorm (byte b)
	Decodes a normalization factor stored in an index.

static float[]	GetNormDecoder ()
	Returns a table for decoding normalization bytes.

static byte	EncodeNorm (float f)
	Encodes a normalization factor for storage in an index.

Public Attributes
const int	NO_DOC_ID_PROVIDED = - 1

Protected Member Functions
	Similarity ()

Properties
static Similarity	Default `[get, set]`
	Gets or sets the default Similarity implementation used by indexing and search code. This is initially an instance of DefaultSimilarity.

Detailed Description

Expert: Scoring API.

Subclasses implement search scoring.

The score of query q for document d correlates to the cosine-distance or dot-product between document and query vectors in a Vector Space Model (VSM) of Information Retrieval. A document whose vector is closer to the query vector in that model is scored higher.

The score is computed as follows:

score(q,d)   =   coord(q,d)  ·  queryNorm(q)  ·	<big><big><big>∑</big></big></big>	<big><big>(</big></big> tf(t in d)  ·  idf(t)²  ·  t.Boost ·  norm(t,d) <big><big>)</big></big>
	t in q

where

tf(t in d) correlates to the term's frequency, defined as the number of times term t appears in the currently scored document d. Documents that have more occurrences of a given term receive a higher score. The default computation for tf(t in d) in DefaultSimilarity is:

 

tf(t in d)   =   frequency^{<big>½</big>}

 
idf(t) stands for Inverse Document Frequency. This value correlates to the inverse of docFreq (the number of documents in which the term t appears). This means rarer terms give higher contribution to the total score. The default computation for idf(t) in DefaultSimilarity is:

 

idf(t)  =   1 + log <big>(</big>

numDocs

–––––––––

docFreq+1

<big>)</big>

 
coord(q,d) is a score factor based on how many of the query terms are found in the specified document. Typically, a document that contains more of the query's terms will receive a higher score than another document with fewer query terms. This is a search time factor computed in coord(q,d) by the Similarity in effect at search time.

queryNorm(q) is a normalizing factor used to make scores between queries comparable. This factor does not affect document ranking (since all ranked documents are multiplied by the same factor), but rather just attempts to make scores from different queries (or even different indexes) comparable. This is a search time factor computed by the Similarity in effect at search time.

The default computation in DefaultSimilarity is:
 

queryNorm(q)   =   queryNorm(sumOfSquaredWeights)   =  

sumOfSquaredWeights^{<big>½</big>}

The sum of squared weights (of the query terms) is computed by the query Lucene.Net.Search.Weight object. For example, a boolean query computes this value as:

GetSumOfSquaredWeights   =   q.Boost ^<big>2</big>  ·	<big><big><big>∑</big></big></big>	<big><big>(</big></big> idf(t)  ·  t.Boost <big><big>) ² </big></big>
	t in q

t.Boost is a search time boost of term t in the query q as specified in the query text (see query syntax), or as set by application calls to Lucene.Net.Search.Query.Boost. Notice that there is really no direct API for accessing a boost of one term in a multi term query, but rather multi terms are represented in a query as multi TermQuery objects, and so the boost of a term in the query is accessible by calling the sub-query Lucene.Net.Search.Query.Boost.
 
norm(t,d) encapsulates a few (indexing time) boost and length factors:
- Document boost - set by calling doc.Boost before adding the document to the index.
- Field boost - set by calling field.Boost before adding the field to a document.
- LengthNorm(field) - 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.
When a document is added to the index, all the above factors are multiplied. If the document has multiple fields with the same name, all their boosts are multiplied together:

 

norm(t,d)   =   doc.Boost  ·  LengthNorm(field)  ·  <big><big><big>∏</big></big></big> field.Boost

field f in d named as t

 
However the resulted norm value is encoded as a single byte before being stored. At search time, the norm byte value is read from the index directory and decoded back to a float norm value. This encoding/decoding, while reducing index size, comes with the price of precision loss - it is not guaranteed that decode(encode(x)) = x. For instance, decode(encode(0.89)) = 0.75. Also notice that search time is too late to modify this norm part of scoring, e.g. by using a different Similarity for search.

See Also: Default

See Also: Lucene.Net.Index.IndexWriter.Similarity

See Also: Searcher.Similarity

Definition at line 293 of file Similarity.cs.

Constructor & Destructor Documentation

Lucene.Net.Search.Similarity.Similarity ( )

protected

Definition at line 295 of file Similarity.cs.

Member Function Documentation

virtual float Lucene.Net.Search.Similarity.ComputeNorm	(	System.String	field,
		FieldInvertState	state
	)

virtual

Compute the normalization value for a field, given the accumulated state of term processing for this field (see FieldInvertState).

Implementations should calculate a float value based on the field state and then return that value.

For backward compatibility this method by default calls LengthNorm(String, int) passing FieldInvertState.Length as the second argument, and then multiplies this value by FieldInvertState.Boost.

WARNING: This API is new and experimental and may suddenly change.

Parameters

field	field name
state	current processing state for this field

Returns: the calculated float norm

Reimplemented in Lucene.Net.Search.DefaultSimilarity, and Lucene.Net.Search.SimilarityDelegator.

Definition at line 437 of file Similarity.cs.

abstract float Lucene.Net.Search.Similarity.Coord	(	int	overlap,
		int	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 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.

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.Net.Search.DefaultSimilarity, and Lucene.Net.Search.SimilarityDelegator.

static float Lucene.Net.Search.Similarity.DecodeNorm ( byte b )

static

Decodes a normalization factor stored in an index.

See Also: EncodeNorm(float)

Definition at line 403 of file Similarity.cs.

static byte Lucene.Net.Search.Similarity.EncodeNorm ( float f )

static

Encodes a normalization factor for storage in an index.

The encoding uses a three-bit mantissa, a five-bit exponent, and the zero-exponent point at 15, 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: Lucene.Net.Documents.AbstractField.Boost, Lucene.Net.Util.SmallFloat

Definition at line 498 of file Similarity.cs.

static float [] Lucene.Net.Search.Similarity.GetNormDecoder ( )

static

Returns a table for decoding normalization bytes.

See Also: EncodeNorm(float)

Definition at line 411 of file Similarity.cs.

abstract float Lucene.Net.Search.Similarity.Idf	(	int	docFreq,
		int	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(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.

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.Net.Search.DefaultSimilarity, and Lucene.Net.Search.SimilarityDelegator.

virtual IDFExplanation Lucene.Net.Search.Similarity.IdfExplain	(	Term	term,
		Searcher	searcher
	)

virtual

Computes a score factor for a simple term and returns an explanation for that score factor.

The default implementation uses:

idf(searcher.docFreq(term), searcher.MaxDoc);

Note that Searcher.MaxDoc is used instead of Lucene.Net.Index.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: an IDFExplain object that includes both an idf score factor and an explanation for the term.

<throws> IOException </throws>

Definition at line 582 of file Similarity.cs.

virtual IDFExplanation Lucene.Net.Search.Similarity.IdfExplain	(	ICollection< Term >	terms,
		Searcher	searcher
	)

virtual

Computes a score factor for a phrase.

The default implementation sums the idf factor for each term in the phrase.

Parameters

terms	the terms in the phrase
searcher	the document collection being searched

Returns: an IDFExplain object that includes both an idf score factor for the phrase and an explanation for each term.

<throws> IOException </throws>

Definition at line 606 of file Similarity.cs.

abstract float Lucene.Net.Search.Similarity.LengthNorm	(	System.String	fieldName,
		int	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 implementations of this method usually return smaller values when numTokens is large, and larger values when numTokens is small.

Note that the return values are computed under Lucene.Net.Index.IndexWriter.AddDocument(Lucene.Net.Documents.Document) and then stored using EncodeNorm(float). 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: Lucene.Net.Documents.AbstractField.Boost

Implemented in Lucene.Net.Search.DefaultSimilarity, and Lucene.Net.Search.SimilarityDelegator.

abstract float Lucene.Net.Search.Similarity.QueryNorm ( float 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.Net.Search.DefaultSimilarity, and Lucene.Net.Search.SimilarityDelegator.

virtual float Lucene.Net.Search.Similarity.ScorePayload	(	int	docId,
		System.String	fieldName,
		int	start,
		int	end,
		byte[]	payload,
		int	offset,
		int	length
	)

virtual

Calculate a scoring factor based on the data in the payload. Overriding implementations are responsible for interpreting what is in the payload. Lucene makes no assumptions about what is in the byte array. The default implementation returns 1.

Parameters

docId	The docId currently being scored. If this value is NO_DOC_ID_PROVIDED, then it should be assumed that the PayloadQuery implementation does not provide document information
fieldName	The fieldName of the term this payload belongs to
start	The start position of the payload
end	The end position of the payload
payload	The payload byte array to be scored
offset	The offset into the payload array
length	The length in the array

Returns

An implementation dependent float to be used as a scoring factor

Definition at line 684 of file Similarity.cs.

abstract float Lucene.Net.Search.Similarity.SloppyFreq ( int 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).

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.Slop

Parameters

distance the edit distance of this sloppy phrase match

Returns: the frequency increment for this match

Implemented in Lucene.Net.Search.DefaultSimilarity, and Lucene.Net.Search.SimilarityDelegator.

virtual float Lucene.Net.Search.Similarity.Tf ( int freq )

virtual

Computes a score factor based on a term or phrase's frequency in a document. This value is multiplied by the Idf(int, int) 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).

Parameters

freq	the frequency of a term within a document

Returns: a score factor based on a term's within-document frequency

Definition at line 521 of file Similarity.cs.

abstract float Lucene.Net.Search.Similarity.Tf ( float 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(int, int) 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.

Parameters