Modeling the beyond-topical aspects of relevance are currently gaining popularity in IR evaluation. For example, the discounted cumulated gain (DCG) measure implicitly models some...
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Background: The evaluation of information retrieval techniques has traditionally relied on human judges to determine which documents are relevant to a query and which are not. Thi...
Abstract. Evaluation is crucial for the success of most research domains, and image retrieval is no exception to this. Recently, several benchmarks have been developed for visual i...
We consider the problem of evaluating retrieval systems using a limited number of relevance judgments. Recent work has demonstrated that one can accurately estimate average precis...