This paper investigates the agreement of relevance assessments between official TREC judgments and those generated from an interactive IR experiment. Results show that 63% of docu...
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...
The empirical investigation of the effectiveness of information retrieval (IR) systems requires a test collection, a set of query topics, and a set of relevance judgments made by ...
Taking advantage of the well-known cluster hypothesis that “closely associated documents tend to be relevant to the same request”, we can use inter-document similarity to prov...
Forming test collection relevance judgments from the pooled output of multiple retrieval systems has become the standard process for creating resources such as the TREC, CLEF, and...