A Retrieval Evaluation Methodology for Incomplete Relevance Assessments

In this paper we a propose an extended methodology for laboratory based Information Retrieval evaluation under incomplete relevance assessments. This new protocol aims to identify potential uncertainty during system comparison that may result from incompleteness. We demonstrate how this methodology can lead towards a finer grained analysis of systems. This is advantageous, because the detection of uncertainty during the evaluation process can guide and direct researchers when evaluating new systems over existing and future test collections.

• Type: Conference
• Year: 2007
• Where: ECIR
• Authors: Mark Baillie, Leif Azzopardi, Ian Ruthven
• Keywords: ECIR 2007, Incomplete Relevance Assessments, Information Retrieval Evaluation, Information Technology, Potential Uncertainty