Document Distance for the Automated Expansion of Relevance Judgements for Information Retrieval Evaluation

January 26, 2015 Β· Declared Dead Β· πŸ› Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

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Authors Diego MollΓ‘, Iman Amini, David Martinez arXiv ID 1501.06380 Category cs.IR: Information Retrieval Citations 5 Venue Annual International ACM SIGIR Conference on Research and Development in Information Retrieval Last Checked 4 months ago
Abstract
This paper reports the use of a document distance-based approach to automatically expand the number of available relevance judgements when these are limited and reduced to only positive judgements. This may happen, for example, when the only available judgements are extracted from a list of references in a published review paper. We compare the results on two document sets: OHSUMED, based on medical research publications, and TREC-8, based on news feeds. We show that evaluations based on these expanded relevance judgements are more reliable than those using only the initially available judgements, especially when the number of available judgements is very limited.
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