Search (2 results, page 1 of 1)

  • × author_ss:"Baillie, M."
  • × author_ss:"Ruthven, I."
  1. Baillie, M.; Azzopardi, L.; Ruthven, I.: Evaluating epistemic uncertainty under incomplete assessments (2008) 0.01 
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    Abstract
    The thesis of this study is to propose an extended methodology for laboratory based Information Retrieval evaluation under incomplete relevance assessments. This new methodology aims to identify potential uncertainty during system comparison that may result from incompleteness. The adoption of this methodology is advantageous, because the detection of epistemic uncertainty - the amount of knowledge (or ignorance) we have about the estimate of a system's performance - during the evaluation process can guide and direct researchers when evaluating new systems over existing and future test collections. Across a series of experiments we demonstrate how this methodology can lead towards a finer grained analysis of systems. In particular, we show through experimentation how the current practice in Information Retrieval evaluation of using a measurement depth larger than the pooling depth increases uncertainty during system comparison.
  2. Ruthven, I.; Baillie, M.; Azzopardi, L.; Bierig, R.; Nicol, E.; Sweeney, S.; Yaciki, M.: Contextual factors affecting the utility of surrogates within exploratory search (2008) 0.01 
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    Footnote
    Beitrag eines Themenschwerpunktes "Evaluating exploratory search systems"

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