A critical investigation of recall and precision as measures of retrieval system performance
ACM Transactions on Information Systems (TOIS)
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Using graded relevance assessments in IR evaluation
Journal of the American Society for Information Science and Technology
The overlap problem in content-oriented XML retrieval evaluation
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
The interactive track at INEX 2004
INEX'04 Proceedings of the Third international conference on Initiative for the Evaluation of XML Retrieval
Controlling overlap in content-oriented XML retrieval
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
eXtended cumulated gain measures for the evaluation of content-oriented XML retrieval
ACM Transactions on Information Systems (TOIS)
Contextualization models for XML retrieval
Information Processing and Management: an International Journal
HiXEval: highlighting XML retrieval evaluation
INEX'05 Proceedings of the 4th international conference on Initiative for the Evaluation of XML Retrieval
On effectiveness measures and relevance functions in ranking INEX systems
AIRS'05 Proceedings of the Second Asia conference on Asia Information Retrieval Technology
TRIX 2004: struggling with the overlap
INEX'04 Proceedings of the Third international conference on Initiative for the Evaluation of XML Retrieval
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In this paper we compare the effectiveness scores and system rankings obtained with the inex-2002 metric, the official measure of INEX 2004, and the XCG metrics proposed in [4] and further developed here. For the comparisons, we use simulated runs as we can easily derive the desired system rankings that a reliable measure should produce based on a predefined set of user preferences. The results indicate that the XCG metrics are better suited for comparing systems for the INEX content-only (CO) task, where systems aim to return the highest scoring elements according to the user preferences reflected in a quantisation function, while also aiming to avoid returning overlapping components.