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Inferring Document Relevance via Average Precision Javed A. Aslam
 

Summary: Inferring Document Relevance via Average Precision
Javed A. Aslam
, Emine Yilmaz
College of Computer and Information Science
Northeastern University
360 Huntington Ave, #202 WVH
Boston, MA 02115
{jaa,emine}@ccs.neu.edu
ABSTRACT
We consider the problem of evaluating retrieval systems us-
ing a limited number of relevance judgments. Recent work
has demonstrated that one can accurately estimate aver-
age precision via a judged pool corresponding to a relatively
small random sample of documents. In this work, we demon-
strate that given values or estimates of average precision,
one can accurately infer the relevances of unjudged docu-
ments. Combined, we thus show how one can efficiently and
accurately infer a large judged pool from a relatively small
number of judged documents, thus permitting accurate and
efficient retrieval evaluation on a large scale.

  

Source: Aslam, Javed - College of Computer Science, Northeastern University

 

Collections: Computer Technologies and Information Sciences