Evaluation of IR systems has always been difficult because of the need for manually assessed relevance judgments. The advent of large editor-driven taxonomies on the web opens the...
Steven M. Beitzel, Eric C. Jensen, Abdur Chowdhury...
Information retrieval system evaluation is complicated by the need for manually assessed relevance judgments. Large manually-built directories on the web open the door to new eval...
Steven M. Beitzel, Eric C. Jensen, Abdur Chowdhury...
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 ...
Ranking a set retrieval systems according to their retrieval effectiveness without relying on relevance judgments was first explored by Soboroff et al. [13]. Over the years, a numb...
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...