Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at https://www.ucl.ac.uk/finance/research/rs-contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
Fixed-Cost Pooling Strategies
  • Publication Type:
    Journal article
  • Publication Sub Type:
  • Authors:
    Lipani A, Losada D, Zuccon G, Lupu M
  • Publisher:
    Institute of Electrical and Electronics Engineers
  • Publication date:
  • Pagination:
  • Journal:
    IEEE Transactions on Knowledge and Data Engineering
  • Volume:
  • Status:
    Published online
  • Print ISSN:
  • Keywords:
    Pooling Method, Test Collections, Pool Bias
The empirical nature of Information Retrieval (IR) mandates strong experimental practices. A keystone of such experimental practices is the Cranfield evaluation paradigm. Within this paradigm, the collection of relevance judgments has been the subject of intense scientific investigation. This is because, on one hand, consistent, precise, and numerous judgements are keys to reducing evaluation uncertainty and test collection bias; on the other hand, however, relevance judgements are costly to collect. The selection of which documents to judge for relevance, known as pooling method, has therefore a great impact on IR evaluation. In this paper we focus on the bias introduced by the pooling method, known as pool bias, which affects the reusability of test collections, in particular when building test collections with a limited budget. In this paper we formalize and evaluate a set of 22 pooling strategies based on: traditional strategies, voting systems, retrieval fusion methods, evaluation \measures, and multi-armed bandit models. To do this we run a large-scale evaluation by considering a set of 9 standard TREC test collections, in which we show that the choice of the pooling strategy has significant effects on the cost needed to obtain an unbiased test collection. We also identify the least biased pooling strategy in terms of pool bias according to three IR evaluation measures: AP, NDCG, and P@10.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Dept of Civil, Environ &Geomatic Eng
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by