Evaluating epistemic uncertainty under incomplete assessments

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

• Type: Journal
• Year: 2008
• Where: IPM
• Authors: Mark Baillie, Leif Azzopardi, Ian Ruthven
• Keywords: Incomplete Relevance Assessments, Information Retrieval Evaluation, IPM 2008, Methodology