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Statistical inference in retrieval effectiveness evaluation

Auteur(s)
Savoy, Jacques 
Institut d'informatique 
Date de parution
1997
In
Information Processing & Management
Vol.
4
No
33
De la page
495
A la page
512
Mots-clés
  • INFORMATION-RETRIEVAL
  • RELEVANCE
  • ALGORITHM
  • INFORMATION-RETRIEVAL...

  • RELEVANCE

  • ALGORITHM

Résumé
Evaluation methodology, and particularly its statistical tests associated, plays a central role in the information retrieval domain which maintains a strong empirical tradition. In an effort to evaluate the retrieval effectiveness of a search algorithm, this paper focuses on the average precision over a set of fixed recall values. After reviewing traditional evaluation methodology through the use of examples, this study suggests applying another statistical inference methodology called bootstrap, within which no particular assumption is needed about the distribution of the observations. Moreover, this scheme may be used to assert the accuracy of virtually any statistic, to build approximate confidence interval, and to verify whether a statistically significant difference exists between two retrieval schemes, even when dealing with a relatively small sample size. This study also suggests selecting the sample median rather than the sample mean in evaluating retrieval effectiveness where the justification for this choice is based on the nature of the information retrieval data. (C) 1997 Elsevier Science Ltd.
Identifiants
https://libra.unine.ch/handle/123456789/6437
Type de publication
journal article
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