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SimpleKLScoreFunc Class Reference

Simple KL-divergence scoring function. More...

#include <SimpleKLRetMethod.hpp>

Inheritance diagram for SimpleKLScoreFunc:

ScoreFunction List of all members.

Public Methods

void setScoreMethod (enum SimpleKLParameter::adjustedScoreMethods adj)
virtual double matchedTermWeight (const QueryTerm *qTerm, const TextQueryRep *qRep, const DocInfo *info, const DocumentRep *dRep) const
 compute the score contribution of a matched term

virtual double adjustedScore (double origScore, const TextQueryRep *qRep, const DocumentRep *dRep) const
 score adjustment (e.g., appropriate length normalization)


Public Attributes

enum SimpleKLParameter::adjustedScoreMethods adjScoreMethod

Detailed Description

Simple KL-divergence scoring function.

The KL-divergence formula D(model_q || model_d), when used for ranking documents, can be computed efficiently by re-writing the formula as a sum over all matched terms in a query and a document. The details of such rewriting are described in the following two papers:


Member Function Documentation

virtual double SimpleKLScoreFunc::adjustedScore double    origScore,
const TextQueryRep   qRep,
const DocumentRep   dRep
const [inline, virtual]
 

score adjustment (e.g., appropriate length normalization)

Reimplemented from ScoreFunction.

virtual double SimpleKLScoreFunc::matchedTermWeight const QueryTerm   qTerm,
const TextQueryRep   qRep,
const DocInfo   info,
const DocumentRep   dRep
const [inline, virtual]
 

compute the score contribution of a matched term

Reimplemented from ScoreFunction.

void SimpleKLScoreFunc::setScoreMethod enum SimpleKLParameter::adjustedScoreMethods    adj [inline]
 


Member Data Documentation

enum SimpleKLParameter::adjustedScoreMethods SimpleKLScoreFunc::adjScoreMethod
 


The documentation for this class was generated from the following file:
Generated on Wed Nov 3 12:59:55 2004 for Lemur Toolkit by doxygen1.2.18