In this paper we a propose an extended methodology for laboratory based Information Retrieval evaluation under in complete 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.
|Title of host publication||Advances in Information Retrieval: 29th European Conference on IR Research (ECIR 2007)|
|Number of pages||12|
|Publication status||Published - 2007|
|Name||Lecture Notes in Computer Science|
- information retrieval
- document retrieval
- relevance ranking
Baillie, M., Azzopardi, L., & Ruthven, I. (2007). A retrieval evaluation methodology for incomplete relevance assessments. In Advances in Information Retrieval: 29th European Conference on IR Research (ECIR 2007) (Vol. 4425). (Lecture Notes in Computer Science). Springer.