Test collections are the primary drivers of progress in information retrieval. They provide a yardstick for assessing the effectiveness of ranking functions in an automatic, rapi...
Nima Asadi, Donald Metzler, Tamer Elsayed, Jimmy L...
Classification problems are traditionally focused on uniclass samples, that is, each sample of the training and test sets has one unique label, which is the target of the classific...
We address the problem of evaluating the risk of a given model accurately at minimal labeling costs. This problem occurs in situations in which risk estimates cannot be obtained f...
Christoph Sawade, Niels Landwehr, Steffen Bickel, ...
Automatic categorization of videos in a Web-scale unconstrained collection such as YouTube is a challenging task. A key issue is how to build an effective training set in the pres...
Zheshen Wang, Ming Zhao, Yang Song, Sanjiv Kumar, ...
This paper addresses the problem of categorizing terms or lexical entities into a predefined set of semantic domains exploiting the knowledge available on-line in the Web. The prop...
Leonardo Rigutini, Ernesto Di Iorio, Marco Ernande...