xapian-core  1.4.20
Public Member Functions | Private Member Functions | Private Attributes | List of all members
Xapian::BM25Weight Class Reference

Xapian::Weight subclass implementing the BM25 probabilistic formula. More...

#include <weight.h>

+ Inheritance diagram for Xapian::BM25Weight:
+ Collaboration diagram for Xapian::BM25Weight:

Public Member Functions

 BM25Weight (double k1, double k2, double k3, double b, double min_normlen)
 Construct a BM25Weight. More...
 
 BM25Weight ()
 
std::string name () const
 Return the name of this weighting scheme. More...
 
std::string serialise () const
 Return this object's parameters serialised as a single string. More...
 
BM25Weightunserialise (const std::string &serialised) const
 Unserialise parameters. More...
 
double get_sumpart (Xapian::termcount wdf, Xapian::termcount doclen, Xapian::termcount uniqterm) const
 Calculate the weight contribution for this object's term to a document. More...
 
double get_maxpart () const
 Return an upper bound on what get_sumpart() can return for any document. More...
 
double get_sumextra (Xapian::termcount doclen, Xapian::termcount uniqterms) const
 Calculate the term-independent weight component for a document. More...
 
double get_maxextra () const
 Return an upper bound on what get_sumextra() can return for any document. More...
 
- Public Member Functions inherited from Xapian::Weight
 Weight ()
 Default constructor, needed by subclass constructors. More...
 
virtual ~Weight ()
 Virtual destructor, because we have virtual methods. More...
 

Private Member Functions

BM25Weightclone () const
 Clone this object. More...
 
void init (double factor)
 Allow the subclass to perform any initialisation it needs to. More...
 

Private Attributes

Xapian::doclength len_factor
 Factor to multiply the document length by. More...
 
double termweight
 Factor combining all the document independent factors. More...
 
double param_k1
 The BM25 parameters. More...
 
double param_k2
 
double param_k3
 
double param_b
 
Xapian::doclength param_min_normlen
 The minimum normalised document length value. More...
 

Additional Inherited Members

- Public Types inherited from Xapian::Weight
enum  type_smoothing {
  TWO_STAGE_SMOOTHING = 1, DIRICHLET_SMOOTHING = 2, ABSOLUTE_DISCOUNT_SMOOTHING = 3, JELINEK_MERCER_SMOOTHING = 4,
  DIRICHLET_PLUS_SMOOTHING = 5
}
 Type of smoothing to use with the Language Model Weighting scheme. More...
 
- Protected Types inherited from Xapian::Weight
enum  stat_flags {
  COLLECTION_SIZE = 1, RSET_SIZE = 2, AVERAGE_LENGTH = 4, TERMFREQ = 8,
  RELTERMFREQ = 16, QUERY_LENGTH = 32, WQF = 64, WDF = 128,
  DOC_LENGTH = 256, DOC_LENGTH_MIN = 512, DOC_LENGTH_MAX = 1024, WDF_MAX = 2048,
  COLLECTION_FREQ = 4096, UNIQUE_TERMS = 8192, TOTAL_LENGTH = COLLECTION_SIZE | AVERAGE_LENGTH
}
 Stats which the weighting scheme can use (see need_stat()). More...
 
- Protected Member Functions inherited from Xapian::Weight
void need_stat (stat_flags flag)
 Tell Xapian that your subclass will want a particular statistic. More...
 
 Weight (const Weight &)
 Don't allow copying. More...
 
Xapian::doccount get_collection_size () const
 The number of documents in the collection. More...
 
Xapian::doccount get_rset_size () const
 The number of documents marked as relevant. More...
 
Xapian::doclength get_average_length () const
 The average length of a document in the collection. More...
 
Xapian::doccount get_termfreq () const
 The number of documents which this term indexes. More...
 
Xapian::doccount get_reltermfreq () const
 The number of relevant documents which this term indexes. More...
 
Xapian::termcount get_collection_freq () const
 The collection frequency of the term. More...
 
Xapian::termcount get_query_length () const
 The length of the query. More...
 
Xapian::termcount get_wqf () const
 The within-query-frequency of this term. More...
 
Xapian::termcount get_doclength_upper_bound () const
 An upper bound on the maximum length of any document in the database. More...
 
Xapian::termcount get_doclength_lower_bound () const
 A lower bound on the minimum length of any document in the database. More...
 
Xapian::termcount get_wdf_upper_bound () const
 An upper bound on the wdf of this term. More...
 
Xapian::totallength get_total_length () const
 Total length of all documents in the collection. More...
 

Detailed Description

Xapian::Weight subclass implementing the BM25 probabilistic formula.

Definition at line 535 of file weight.h.

Constructor & Destructor Documentation

◆ BM25Weight() [1/2]

Xapian::BM25Weight::BM25Weight ( double  k1,
double  k2,
double  k3,
double  b,
double  min_normlen 
)
inline

Construct a BM25Weight.

Parameters
k1A non-negative parameter controlling how influential within-document-frequency (wdf) is. k1=0 means that wdf doesn't affect the weights. The larger k1 is, the more wdf influences the weights. (default 1)
k2A non-negative parameter which controls the strength of a correction factor which depends upon query length and normalised document length. k2=0 disable this factor; larger k2 makes it stronger. (default 0)
k3A non-negative parameter controlling how influential within-query-frequency (wqf) is. k3=0 means that wqf doesn't affect the weights. The larger k3 is, the more wqf influences the weights. (default 1)
bA parameter between 0 and 1, controlling how strong the document length normalisation of wdf is. 0 means no normalisation; 1 means full normalisation. (default 0.5)
min_normlenA parameter specifying a minimum value for normalised document length. Normalised document length values less than this will be clamped to this value, helping to prevent very short documents getting large weights. (default 0.5)

Definition at line 580 of file weight.h.

◆ BM25Weight() [2/2]

Xapian::BM25Weight::BM25Weight ( )
inline

Definition at line 607 of file weight.h.

References name.

Member Function Documentation

◆ clone()

BM25Weight * Xapian::BM25Weight::clone ( ) const
privatevirtual

Clone this object.

This method allocates and returns a copy of the object it is called on.

If your subclass is called FooWeight and has parameters a and b, then you would implement FooWeight::clone() like so:

FooWeight * FooWeight::clone() const { return new FooWeight(a, b); }

Note that the returned object will be deallocated by Xapian after use with "delete". If you want to handle the deletion in a special way (for example when wrapping the Xapian API for use from another language) then you can define a static operator delete method in your subclass as shown here: https://trac.xapian.org/ticket/554#comment:1

Implements Xapian::Weight.

Definition at line 39 of file bm25weight.cc.

◆ get_maxextra()

double Xapian::BM25Weight::get_maxextra ( ) const
virtual

Return an upper bound on what get_sumextra() can return for any document.

This information is used by the matcher to perform various optimisations, so strive to make the bound as tight as possible.

Implements Xapian::Weight.

Definition at line 221 of file bm25weight.cc.

References LOGCALL, and RETURN.

◆ get_maxpart()

double Xapian::BM25Weight::get_maxpart ( ) const
virtual

Return an upper bound on what get_sumpart() can return for any document.

This information is used by the matcher to perform various optimisations, so strive to make the bound as tight as possible.

Implements Xapian::Weight.

Definition at line 177 of file bm25weight.cc.

References AssertRel, LOGCALL, and RETURN.

◆ get_sumextra()

double Xapian::BM25Weight::get_sumextra ( Xapian::termcount  doclen,
Xapian::termcount  uniqterms 
) const
virtual

Calculate the term-independent weight component for a document.

The parameter gives information about the document which may be used in the calculations:

Parameters
doclenThe document's length (unnormalised).
uniqtermsThe number of unique terms in the document.

Implements Xapian::Weight.

Definition at line 213 of file bm25weight.cc.

References LOGCALL, and RETURN.

◆ get_sumpart()

double Xapian::BM25Weight::get_sumpart ( Xapian::termcount  wdf,
Xapian::termcount  doclen,
Xapian::termcount  uniqterms 
) const
virtual

Calculate the weight contribution for this object's term to a document.

The parameters give information about the document which may be used in the calculations:

Parameters
wdfThe within document frequency of the term in the document.
doclenThe document's length (unnormalised).
uniqtermsNumber of unique terms in the document (used for absolute smoothing).

Implements Xapian::Weight.

Definition at line 164 of file bm25weight.cc.

References AssertRel, LOGCALL, and RETURN.

◆ init()

void Xapian::BM25Weight::init ( double  factor)
privatevirtual

Allow the subclass to perform any initialisation it needs to.

Parameters
factorAny scaling factor (e.g. from OP_SCALE_WEIGHT). If the Weight object is for the term-independent weight supplied by get_sumextra()/get_maxextra(), then init(0.0) is called (starting from Xapian 1.2.11 and 1.3.1 - earlier versions failed to call init() for such Weight objects).

Implements Xapian::Weight.

Definition at line 46 of file bm25weight.cc.

References AssertRel, LOGVALUE, and rare.

◆ name()

string Xapian::BM25Weight::name ( ) const
virtual

Return the name of this weighting scheme.

This name is used by the remote backend. It is passed along with the serialised parameters to the remote server so that it knows which class to create.

Return the full namespace-qualified name of your class here - if your class is called FooWeight, return "FooWeight" from this method (Xapian::BM25Weight returns "Xapian::BM25Weight" here).

If you don't want to support the remote backend, you can use the default implementation which simply returns an empty string.

Reimplemented from Xapian::Weight.

Definition at line 132 of file bm25weight.cc.

Referenced by DEFINE_TESTCASE().

◆ serialise()

string Xapian::BM25Weight::serialise ( ) const
virtual

Return this object's parameters serialised as a single string.

If you don't want to support the remote backend, you can use the default implementation which simply throws Xapian::UnimplementedError.

Reimplemented from Xapian::Weight.

Definition at line 138 of file bm25weight.cc.

References serialise_double().

Referenced by DEFINE_TESTCASE().

◆ unserialise()

BM25Weight * Xapian::BM25Weight::unserialise ( const std::string &  serialised) const
virtual

Unserialise parameters.

This method unserialises parameters serialised by the serialise() method and allocates and returns a new object initialised with them.

If you don't want to support the remote backend, you can use the default implementation which simply throws Xapian::UnimplementedError.

Note that the returned object will be deallocated by Xapian after use with "delete". If you want to handle the deletion in a special way (for example when wrapping the Xapian API for use from another language) then you can define a static operator delete method in your subclass as shown here: https://trac.xapian.org/ticket/554#comment:1

Parameters
serialisedA string containing the serialised parameters.

Reimplemented from Xapian::Weight.

Definition at line 149 of file bm25weight.cc.

References rare, and unserialise_double().

Referenced by DEFINE_TESTCASE().

Member Data Documentation

◆ len_factor

Xapian::doclength Xapian::BM25Weight::len_factor
mutableprivate

Factor to multiply the document length by.

Definition at line 537 of file weight.h.

◆ param_b

double Xapian::BM25Weight::param_b
private

Definition at line 543 of file weight.h.

◆ param_k1

double Xapian::BM25Weight::param_k1
private

The BM25 parameters.

Definition at line 543 of file weight.h.

◆ param_k2

double Xapian::BM25Weight::param_k2
private

Definition at line 543 of file weight.h.

◆ param_k3

double Xapian::BM25Weight::param_k3
private

Definition at line 543 of file weight.h.

◆ param_min_normlen

Xapian::doclength Xapian::BM25Weight::param_min_normlen
private

The minimum normalised document length value.

Definition at line 546 of file weight.h.

◆ termweight

double Xapian::BM25Weight::termweight
mutableprivate

Factor combining all the document independent factors.

Definition at line 540 of file weight.h.


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