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SimpleKLScoreFunc Class Reference

Simple KL-divergence scoring function. More...

#include <SimpleKLRetMethod.hpp>

Inheritance diagram for SimpleKLScoreFunc:

List of all members.

Public Methods
virtual double	matchedTermWeight (QueryTerm *qTerm,TextQueryRep *qRep,DocInfo *info,DocumentRep *dRep)
	compute the score contribution of a matched term.
virtual double	adjustedScore (double origScore,TextQueryRep *qRep,DocumentRep *dRep)
	score adjustment (e.g., appropriate length normalization).

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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:

• C. Zhai and J. Lafferty. A study of smoothing methods for language models applied to ad hoc information retrieval, In 24th ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR'01), 2001.
• P. Ogilvie and J. Callan. Experiments using the Lemur toolkit. In Proceedings of the Tenth Text Retrieval Conference (TREC-10).

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Member Function Documentation

double SimpleKLScoreFunc::adjustedScore ( double origScore, TextQueryRep * qRep, DocumentRep * dRep ) [inline, virtual]

score adjustment (e.g., appropriate length normalization). Reimplemented from ScoreFunction.

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

compute the score contribution of a matched term. Reimplemented from ScoreFunction.

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

• SimpleKLRetMethod.hpp

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