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...
Background: When term ambiguity and variability are very high, dictionary-based Named Entity Recognition (NER) is not an ideal solution even though large-scale terminological reso...
Yutaka Sasaki, Yoshimasa Tsuruoka, John McNaught, ...
We are building an interactive, visual text analysis tool that aids users in analyzing a large collection of text. Unlike existing work in text analysis, which focuses either on d...
In many Web applications, such as blog classification and newsgroup classification, labeled data are in short supply. It often happens that obtaining labeled data in a new domain ...
In a recent work, Mangard et al. showed that under certain assumptions, the (so-called) standard univariate side-channel attacks using a distance-of-means test, correlation analysi...