This class implements the PL2 weighting scheme. More...
Inheritance diagram for Xapian::PL2Weight:
Public Member Functions | |
| PL2Weight (double c) | |
| Construct a PL2Weight. More... | |
| 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... | |
| PL2Weight * | unserialise (const std::string &serialised) const |
| Unserialise parameters. More... | |
| 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. 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. | |
| virtual | ~Weight () |
| Virtual destructor, because we have virtual methods. 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 } |
| 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. | |
| 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 |
| 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. 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... | |
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
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explicit |
Construct a PL2Weight.
- Parameters
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c A non-negative and non zero 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
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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.
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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.
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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
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doclen The document's length (unnormalised). uniqterms The number of unique terms in the document.
Implements Xapian::Weight.
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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
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wdf The within document frequency of the term in the document. doclen The document's length (unnormalised). uniqterms Number of unique terms in the document (used for absolute smoothing).
Implements Xapian::Weight.
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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.
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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.
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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
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serialised A string containing the serialised parameters.
Reimplemented from Xapian::Weight.
The documentation for this class was generated from the following file:
- xapian/weight.h