Susanne Wolff

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This study exploits statistical redundancy inherent in natural language to automatically predict scores for essays. We use a hybrid feature identification method, including syntactic structure analysis, rhetorical structure analysis, and topical analysis, to score essay responses from test-takers of the Graduate Management Admissions Test (GMAT) and the(More)
This paper discusses a case study in which lexical semantic techniques were used to implement a prototype scoring system for short-answer, free-responses to test questions. Scoring, as it is discussed in this paper, is a kind of classification problem. Responses are automatically scored by being assigned appropriate classifications. The ultimate goal is to(More)
Electronic Essay Rater (e-rater) is a prototype automated essay scoring system built at Educational Testing Service (ETS) that uses discourse marking, in addition to syntactic information and topical content vector analyses to automatically assign essay scores. This paper gives a general description ore-rater as a whole, but its emphasis is on the(More)
We present a method for automatically detecting missing hyphens in English text. Our method goes beyond a purely dictionary-based approach and also takes context into account. We evaluate our model on artificially generated data as well as naturally occurring learner text. Our best-performing model achieves high precision and reasonable recall, making it(More)
With the emergence of mass spectrometry in protein science and the availability of complete genome sequences, proteomics has gone through a rapid development. The soil bacterium Bacillus subtilis, as one of the first DNA sequenced species, represents a model for Gram-positive bacteria and its proteome was extensively studied throughout the years. Having the(More)
The analysis of integral membrane proteins (IMPs) with mass spectrometry-centered technologies has undergone great progress during the past few years, allowing for the analysis of several hundreds of IMPs. In this study, we investigated three promising shotgun approaches for the identification of IMPs of the model organism Bacillus subtilis. One comprises a(More)
The proteome of exponentially growing Bacillus subtilis cells was dissected by the implementation of shotgun proteomics and a semigel-based approach for a particular exploration of membrane proteins. The current number of 745 protein identifications that was gained by the use of two-dimensional gel electrophoresis could be increased by 473 additional(More)
Staphylococcus aureus is a versatile human pathogen causing a wide variety of diseases ranging from wound infection to endocarditis, osteomyelitis, and sepsis. In order to investigate this pathogen, we sought to analyze the cytoplasmic proteome of S. aureus COL by using two different approaches: two-dimensional (2D) gel analyses combined with(More)
The Gram-positive bacterium Staphylococcus aureus is a serious human pathogen causing a wide variety of diseases, and its increasing resistance toward all available antibiotics makes its further investigation absolutely essential. We examined the membrane proteome of exponentially growing cells of S. aureus COL because this subproteome plays a major role in(More)
Developing more shareable resources to support natural language analysis will make it easier and cheaper to create new language processing applications and to support research in computational linguistics. One natural candidate for such a resource is a broad-coverage dictionary, since the work required to create such a dictionary is large but there is(More)