xapian-core  1.4.25
Public Member Functions | List of all members
Xapian::PL2Weight Class Reference

This class implements the PL2 weighting scheme. More...

#include <weight.h>

+ Inheritance diagram for Xapian::PL2Weight:

Public Member Functions

 PL2Weight (double c)
 Construct a PL2Weight.
 
std::string name () const
 Return the name of this weighting scheme.
 
std::string serialise () const
 Return this object's parameters serialised as a single string.
 
PL2Weightunserialise (const std::string &serialised) const
 Unserialise parameters.
 
double get_sumpart (Xapian::termcount wdf, Xapian::termcount doclen, Xapian::termcount uniqterms) const
 Calculate the weight contribution for this object's term to a document.
 
double get_maxpart () const
 Return an upper bound on what get_sumpart() can return for any document.
 
double get_sumextra (Xapian::termcount doclen, Xapian::termcount uniqterms) const
 Calculate the term-independent weight component for a document.
 
double get_maxextra () const
 Return an upper bound on what get_sumextra() can return for any document.
 
- Public Member Functions inherited from Xapian::Weight
 Weight ()
 Default constructor, needed by subclass constructors.
 
virtual ~Weight ()
 Virtual destructor, because we have virtual methods.
 

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.
 
 Weight (const Weight &)
 Don't allow copying.
 
Xapian::doccount get_collection_size () const
 The number of documents in the collection.
 
Xapian::doccount get_rset_size () const
 The number of documents marked as relevant.
 
Xapian::doclength get_average_length () const
 The average length of a document in the collection.
 
Xapian::doccount get_termfreq () const
 The number of documents which this term indexes.
 
Xapian::doccount get_reltermfreq () const
 The number of relevant documents which this term indexes.
 
Xapian::termcount get_collection_freq () const
 The collection frequency of the term.
 
Xapian::termcount get_query_length () const
 The length of the query.
 
Xapian::termcount get_wqf () const
 The within-query-frequency of this term.
 
Xapian::termcount get_doclength_upper_bound () const
 An upper bound on the maximum length of any document in the database.
 
Xapian::termcount get_doclength_lower_bound () const
 A lower bound on the minimum length of any document in the database.
 
Xapian::termcount get_wdf_upper_bound () const
 An upper bound on the wdf of this term.
 
Xapian::totallength get_total_length () const
 Total length of all documents in the collection.
 

Detailed Description

This class implements the PL2 weighting scheme.

PL2 is a representative scheme of the Divergence from Randomness Framework by Gianni Amati.

This weighting scheme is useful for tasks that require early precision.

It uses the Poisson approximation of the Binomial Probabilistic distribution (P) along with Stirling's approximation for the factorial value, the Laplace method to find the aftereffect of sampling (L) and the second wdf normalization proposed by Amati to normalize the wdf in the document to the length of the document (H2).

For more information about the DFR Framework and the PL2 scheme, please refer to : Gianni Amati and Cornelis Joost Van Rijsbergen Probabilistic models of information retrieval based on measuring the divergence from randomness ACM Transactions on Information Systems (TOIS) 20, (4), 2002, pp. 357-389.

Constructor & Destructor Documentation

◆ PL2Weight()

Xapian::PL2Weight::PL2Weight ( double  c)
explicit

Construct a PL2Weight.

Parameters
cA strictly positive parameter controlling the extent of the normalization of the wdf to the document length. The default value of 1 is suitable for longer queries but it may need to be changed for shorter queries. For more information, please refer to Gianni Amati's PHD thesis titled Probabilistic Models for Information Retrieval based on Divergence from Randomness.

Member Function Documentation

◆ get_maxextra()

double Xapian::PL2Weight::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.

◆ get_maxpart()

double Xapian::PL2Weight::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.

◆ get_sumextra()

double Xapian::PL2Weight::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.

◆ get_sumpart()

double Xapian::PL2Weight::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.

◆ name()

std::string Xapian::PL2Weight::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.

◆ serialise()

std::string Xapian::PL2Weight::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.

◆ unserialise()

PL2Weight * Xapian::PL2Weight::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.


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