Baillie, M., Azzopardi, L. and Ruthven, I. (2007) A retrieval evaluation methodology for incomplete relevance assessments. Lecture Notes in Computer Science, 4425, pp. 271-282. (doi: 10.1007/978-3-540-71496-5_26)
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Abstract
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.
Item Type: | Articles |
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Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Azzopardi, Dr Leif |
Authors: | Baillie, M., Azzopardi, L., and Ruthven, I. |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
College/School: | College of Science and Engineering > School of Computing Science |
Journal Name: | Lecture Notes in Computer Science |
ISSN: | 0302-9743 |
ISSN (Online): | 1611-3349 |
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