With the rapid proliferation of Web 2.0, user-generated content (UGC), which is formed by the public to reflect their views and voice, presents rich and timely feedback on news events. Existing research either studies the common and private features between news and UGC, or describes the ability of news media to influence the public opinion. However, in the current highly media-user interactive...

Domain dependence of NLP systems is one of the major obstacles to their application in large-scale text analysis, also restricting the applicability of FrameNet semantic role labeling (SRL) systems. Yet, current FrameNet SRL systems are still only evaluated on a single in-domain test set. For the first time, we study the domain dependence of FrameNet SRL on a wide range of benchmark sets. We cr...

The goal of machine learning is to develop predictors that generalize well to test data. Ideally, this is achieved by training on an almost infinitely large training data set that captures all variations in the data distribution. In practical learning settings, however, we do not have infinite data and our predictors may overfit. Overfitting may be combatted, for example, by adding a regularize...

The paper presents first results of a project that aims at building a model-based tool for functional testing of control software for passenger vehicles. The objective is that this tool can be used in today’s engineering practice and, hence, the approach must not require costly changes in the current test generation process and not assume data and skills that do not exist in reality. We focus o...