In this paper we build user simulations of older and younger adults using a corpus of interactions with a Wizard-of-Oz appointment scheduling system. We measure the quality of the...
Kallirroi Georgila, Maria Wolters, Johanna D. Moor...
Active learning is a machine learning approach to achieving high-accuracy with a small amount of labels by letting the learning algorithm choose instances to be labeled. Most of p...
Supervised word sense disambiguation requires training corpora that have been tagged with word senses, which begs the question of which word senses to tag with. The default choice...
Current re-ranking algorithms for machine translation rely on log-linear models, which have the potential problem of underfitting the training data. We present BoostedMERT, a nove...
Computing confidence scores for applications, such as dialogue system, information retrieving and extraction, is an active research area. However, its focus has been primarily on ...
Researchers typically evaluate word prediction using keystroke savings, however, this measure is not straightforward. We present several complications in computing keystroke savin...
Relation extraction is the task of finding semantic relations between two entities from text. In this paper, we propose a novel feature-based Chinese relation extraction approach ...
In this paper we describe recent improvements to components and methods used in our statistical machine translation system for ChineseEnglish used in the January 2008 GALE evaluat...
Almut Silja Hildebrand, Kay Rottmann, Mohamed Noam...
Traditional Active Learning (AL) techniques assume that the annotation of each datum costs the same. This is not the case when annotating sequences; some sequences will take longe...
Robbie Haertel, Eric K. Ringger, Kevin D. Seppi, J...