ness, concreteness, staticness, or dynamism. The other grammar-based approach to assessing stylistic goals was implemented by Ryan et al. (1992). The stylistic goals of this grammar (with settings in brackets) are as follows: emphasis (emphatic, neutral, at); clarity (clear, neutral, obscure); and dynamism (dynamic, neutral, static). In this grammar, the basis for evaluating these goals was sem...

Previous work on statistical language generation has primarily focused on grammaticality and naturalness, scoring generation possibilities according to a language model or user feedback. More recent work has investigated data-driven techniques for controlling linguistic style without overgeneration, by reproducing variation dimensions extracted from corpora. Another line of work has produced ha...

Lexica l Syn t ac t i c Se ma n t i c Stylistic Stylistic Stylistic G r a m m a r G r a m m a r G r a m m a r Figure 1 A stylistic grammar. of primitive stylistic elements and rules for combining them. At the central level, we use a single vocabulary of abstract elements, stylistic terms that are maximally expressive. Rules relate these abstract elements to patterns of lexical, syntactic, and s...

Submitted for the DFD14 Meeting of The American Physical Society Frequency-Domain DSMC Method for Oscillatory Gas Flows DANIEL LADIGES, JOHN SADER, The University of Melbourne — Gas flows generated by resonating nanoscale devices inherently occur in the non-continuum, low Mach number regime. Numerical simulation of such flows presents a tremendous challenge, which has motivated the development ...

User interfaces to WWW search engines typically present results as ranked lists of documents. Such lists give users little help in understanding document variation: we propose a richer representation of retrieval results in the search interface. Fundamental to us is the notion of document grouping. We use both stylistic genre-based document categorization and statistical content-based clusterin...

Introduction Early researchers in authorship attribution used a variety of statistical methods to identify stylistic discriminators – characteristics which remain approximately invariant within the works of a given author but which tend to vary from author to author (Holmes 1998, McEnery & Oakes 2000). In recent years machine learning methods have been applied to authorship attribution. A few e...