Leibniz University of Hanover

About: Leibniz University of Hanover is a education organization based out in Hanover, Niedersachsen, Germany. It is known for research contribution in the topics: Finite element method & Computer science. The organization has 14283 authors who have published 29845 publications receiving 682152 citations.

Boilerplate detection using shallow text features

Abstract: In addition to the actual content Web pages consist of navigational elements, templates, and advertisements. This boilerplate text typically is not related to the main content, may deteriorate search precision and thus needs to be detected properly. In this paper, we analyze a small set of shallow text features for classifying the individual text elements in a Web page. We compare the approach to complex, state-of-the-art techniques and show that competitive accuracy can be achieved, at almost no cost. Moreover, we derive a simple and plausible stochastic model for describing the boilerplate creation process. With the help of our model, we also quantify the impact of boilerplate removal to retrieval performance and show significant improvements over the baseline. Finally, we extend the principled approach by straight-forward heuristics, achieving a remarkable detection accuracy.

An intercomparison of large-eddy simulations of the stable boundary layer

Abstract: Results are presented from the first intercomparison of large-eddy simulation (LES) models for the stable boundary layer (SBL), as part of the Global Energy and Water Cycle Experiment Atmospheric Boundary Layer Study initiative. A moderately stable case is used, based on Arctic observations. All models produce successful simulations, in as much as they generate resolved turbulence and reflect many of the results from local scaling theory and observations. Simulations performed at 1-m and 2-m resolution show only small changes in the mean profiles compared to coarser resolutions. Also, sensitivity to subgrid models for individual models highlights their importance in SBL simulation at moderate resolution (6.25 m). Stability functions are derived from the LES using typical mixing lengths used in numerical weather prediction (NWP) and climate models. The functions have smaller values than those used in NWP. There is also support for the use of K-profile similarity in parametrizations. Thus, the results provide improved understanding and motivate future developments of the parametrization of the SBL.