We present a pointwise approach to Japanese morphological analysis (MA) that ignores structure information during learning and tagging. Despite the lack of structure, it is able t...
FlyTF (http://www.flytf.org) is a database of computationally predicted and/or experimentally verified site-specific transcription factors (TFs) in the fruit fly Drosophila melano...
Ulrike Pfreundt, Daniel P. James, Susan Tweedie, D...
In this article we want to demonstrate that annotation of multiword expressions in the Prague Dependency Treebank is a well defined task, that it is useful as well as feasible, an...
Protein function prediction is an active area of research in bioinformatics. And yet, transfer of annotation on the basis of sequence or structural similarity remains widely used ...
Abstract We present an active learning framework that predicts the tradeoff between the effort and information gain associated with a candidate image annotation, thereby ranking un...
We describe a Chinese temporal annotation experiment that produced a sizable data set for the TempEval-2 evaluation campaign. We show that while we have achieved high inter-annota...
Active Learning (AL) is a selective sampling strategy which has been shown to be particularly cost-efficient by drastically reducing the amount of training data to be manually ann...
Treebank annotation is a labor-intensive and time-consuming task. In this paper, we show that a simple statistical ranking model can significantly improve treebanking efficiency b...
Annotating scientific publications with keywords and phrases is of great importance to searching, indexing, and cataloging such documents. Unlike previous studies that focused on ...
Active learning has been applied to different NLP tasks, with the aim of limiting the amount of time and cost for human annotation. Most studies on active learning have only simul...