scispace - formally typeset
Search or ask a question
Institution

Bauhaus University, Weimar

EducationWeimar, Thüringen, Germany
About: Bauhaus University, Weimar is a education organization based out in Weimar, Thüringen, Germany. It is known for research contribution in the topics: Finite element method & Isogeometric analysis. The organization has 1421 authors who have published 2998 publications receiving 104454 citations. The organization is also known as: Bauhaus-Universität Weimar & Hochschule für Architektur und Bauwesen.


Papers
More filters
Journal ArticleDOI
01 Jun 2013-Carbon
TL;DR: In this paper, the van der Waals interaction between carbon nanotubes, graphene and substrates is modeled through a continuum model and the dependence of the cohesive energy on their size, spacing and crossing angles is analyzed.

98 citations

Journal ArticleDOI
TL;DR: In this article, the applicability of peridynamics to accurately predict nonlinear transient deformation and damage behavior of composites under shock or blast types of loadings due to explosions was demonstrated.

97 citations

Journal ArticleDOI
TL;DR: The lessons learned at PAN 2010 are reviewed, the method used to construct the corpus is explained, and the work presented here is the first to join the paraphrasing and plagiarism communities.
Abstract: To paraphrase means to rewrite content while preserving the original meaning. Paraphrasing is important in fields such as text reuse in journalism, anonymizing work, and improving the quality of customer-written reviews. This article contributes to paraphrase acquisition and focuses on two aspects that are not addressed by current research: (1) acquisition via crowdsourcing, and (2) acquisition of passage-level samples. The challenge of the first aspect is automatic quality assurance; without such a means the crowdsourcing paradigm is not effective, and without crowdsourcing the creation of test corpora is unacceptably expensive for realistic order of magnitudes. The second aspect addresses the deficit that most of the previous work in generating and evaluating paraphrases has been conducted using sentence-level paraphrases or shorter; these short-sample analyses are limited in terms of application to plagiarism detection, for example. We present the Webis Crowd Paraphrase Corpus 2011 (Webis-CPC-11), which recently formed part of the PAN 2010 international plagiarism detection competition. This corpus comprises passage-level paraphrases with 4067 positive samples and 3792 negative samples that failed our criteria, using Amazon's Mechanical Turk for crowdsourcing. In this article, we review the lessons learned at PAN 2010, and explain in detail the method used to construct the corpus. The empirical contributions include machine learning experiments to explore if passage-level paraphrases can be identified in a two-class classification problem using paraphrase similarity features, and we find that a k-nearest-neighbor classifier can correctly distinguish between paraphrased and nonparaphrased samples with 0.980 precision at 0.523 recall. This result implies that just under half of our samples must be discarded (remaining 0.477 fraction), but our cost analysis shows that the automation we introduce results in a 18p financial saving and over 100 hours of time returned to the researchers when repeating a similar corpus design. On the other hand, when building an unrelated corpus requiring, say, 25p training data for the automated component, we show that the financial outcome is cost neutral, while still returning over 70 hours of time to the researchers. The work presented here is the first to join the paraphrasing and plagiarism communities.

97 citations

Proceedings ArticleDOI
23 Jul 2007
TL;DR: The design principles behind hash-based search methods are revealed and it is shown how optimum hash functions for similarity search can be derived and the rationale of their effectiveness is explained.
Abstract: Hash-based similarity search reduces a continuous similarity relation to the binary concept "similar or not similar": two feature vectors are considered as similar if they are mapped on the same hash key. From its runtime performance this principle is unequaled--while being unaffected by dimensionality concerns at the same time. Similarity hashing is applied with great success for near similarity search in large document collections, and it is considered as a key technology for near-duplicate detection and plagiarism analysis. This papers reveals the design principles behind hash-based search methods and presents them in a unified way. We introduce new stress statistics that are suited to analyze the performance of hash-based search methods, and we explain the rationale of their effectiveness. Based on these insights, we show how optimum hash functions for similarity search can be derived. We also present new results of a comparative study between different hash-based search methods.

97 citations

Journal ArticleDOI
TL;DR: Structural equation modeling demonstrates that studio actions primarily influence early box office results, whereas movie quality influences both short- and long-term theatrical outcomes.
Abstract: We examine the relative roles of marketing actions and product quality in determining commercial success. Using the motion picture context, in which product quality is difficult for consumers to anticipate and information on product success is available for different points in time, we model the effects of studio actions and movie quality on a movie’s sales during different phases of its theatrical run. For a sample of 331 recent motion pictures, structural equation modeling demonstrates that studio actions primarily influence early box office results, whereas movie quality influences both short- and long-term theatrical outcomes. The core results are robust across moderating conditions. We identify two data segments with follow-up latent class regressions and explore the degree of studio actions needed to “save” movies of varying quality. We finally offer some implications for research and management.

97 citations


Authors

Showing all 1443 results

NameH-indexPapersCitations
Timon Rabczuk9972735893
Adri C. T. van Duin7948926911
Paolo Rosso5654112757
Xiaoying Zhuang5427110082
Benno Stein533409880
Jin-Wu Jiang521757661
Gordon Wetzstein512589793
Goangseup Zi451538411
Bohayra Mortazavi441625802
Thorsten Hennig-Thurau4412317542
Jörg Hoffmann402007785
Martin Potthast401906563
Pedro M. A. Areias381075908
Amir Mosavi384326209
Guido De Roeck382748063
Network Information
Related Institutions (5)
Delft University of Technology
94.4K papers, 2.7M citations

83% related

Georgia Institute of Technology
119K papers, 4.6M citations

83% related

Carnegie Mellon University
104.3K papers, 5.9M citations

83% related

Eindhoven University of Technology
52.9K papers, 1.5M citations

82% related

Microsoft
86.9K papers, 4.1M citations

82% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202321
202260
2021224
2020249
2019247
2018273