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Towards A Computational Model Of Frame Of Reference Alignment In Swedish Dialogue, Simon Dobnik, Christine Howes, Kim Demaret, John D. Kelleher

Conference papers

In this paper we examine how people negotiate, interpret and repair the frame of reference (FoR) in online text based dialogues discussing spatial scenes in Swedish. We describe work-in-progress in which participants are given different perspectives of the same scene and asked to locate several objects that are only shown on one of their pictures. This task requires participants to coordinate on FoR in order to identify the missing objects. This study has implications for situated dialogue systems.

Virtual Meatspace: Word Formation And Deformation In Cyberpunk Discussions, Matt Garley, Benjamin Slade

Publications and Research

No abstract provided.

Event Parsing In Narrative: Trials And Tribulations Of Archaic English Fairy Tales, Rebecca Lovering

Dissertations, Theses, and Capstone Projects

While event extraction and automatic summarization have taken great strides in the realm of news stories, fictional narratives like fairy tales have not been so fortunate. A number of challenges arise from the literary elements present in fairy tales that are not found in more straightforward corpora of natural language, such as archaic expressions and sentence structures. To aid in summarization of fictional texts, I created an class - a template for a digital object, in this case a semantic and story event - that captures elements predicted to help classify events as important for inclusion. I wrote a processor …

Language-Mixing In Discourse In Bilingual Individuals With Non-Fluent Aphasia, Avanthi Paplikar

Dissertations, Theses, and Capstone Projects

Language-mixing (LM) as defined by Chengappa (2009, p. 417) is an “intra-sentential phenomenon referred to as the mixing of various linguistic units (morphemes, words, modifiers, phrases, etc.), primarily from two participating grammatical systems”. LM is influenced by grammatical, environmental, and social constraints (e.g., Milroy & Wei, 1995; Bhat & Chengappa, 2005). Researchers have suggested that LM in patients with aphasia is a communicative strategy used to achieve successful exchanges between speakers; the effectiveness of this mixing, however, had yet to be demonstrated quantitatively.

In the current study we investigated whether LM is present in bilingual speakers with aphasia, and if …

Conspiracy And Bias: Argumentative Features And Persuasiveness Of Conspiracy Theories, Steve Oswald

OSSA Conference Archive

This paper deals with the argumentative biases Conspiracy Theories (henceforth CTs) typically suffer from and pursues two goals: (i) the identification of recurring argumentative and rhetorical features of conspiracy theories, which translates into an attempt to elaborate their argumentative profile (see Hansen 2013); (ii) the elaboration of a cognitively-grounded account of CTs in terms of their persuasiveness.

To fulfil goal (i), I examine online instances of different cases of CTs (the Moon hoax, 9/11 as an inside job, chemical trails). Building on the general rhetorical features of CTs identified by Byford (2011: 88-93), I elaborate a first argumentative profile surveying …

Strategies Of Objectification In Opinion Articles: The Case Of Evidentials, Elena Musi

OSSA Conference Archive

This paper investigates lexical evidentials in an English corpus (30 texts) about oil drilling issues in the Adriatic Sea. Lexical evidentials (e.g. see, must, find, evidently) indicate “the kind of justification for a factual claim which is available to the person making that claim […]” (Anderson 1986: 274). They constitute a privileged viewpoint to investigate how and at which degree journalists manage to present their claims as objective since they work as argumentative indicators (Van Eemeren et al. 2007), pointing to inherently subjective (e.g. I find that x) or possibly objective (e.g. It must be …

Hpcnmf: A High-Performance Toolbox For Non-Negative Matrix Factorization, Karthik Devarajan, Guoli Wang

COBRA Preprint Series

Non-negative matrix factorization (NMF) is a widely used machine learning algorithm for dimension reduction of large-scale data. It has found successful applications in a variety of fields such as computational biology, neuroscience, natural language processing, information retrieval, image processing and speech recognition. In bioinformatics, for example, it has been used to extract patterns and profiles from genomic and text-mining data as well as in protein sequence and structure analysis. While the scientific performance of NMF is very promising in dealing with high dimensional data sets and complex data structures, its computational cost is high and sometimes could be critical for …