Norms of speech acts

This paper offers a systematic classification and characterization of speech acts and their norms. Recently, the normative approach has been applied to various speech acts, most notably to constatives. I start by showing how the work on the norms of assertion has influenced various approaches to the norms of other speech acts. I focus on the fact that various norms of assertion have different extensions, i.e., they denote different clusters of illocutions as belonging to an assertion. I argue that this has consequences for theorising about norms of other speech acts and generates certain arbitrary divisions. In the central part, I analyse two groups of speech acts. Firstly, ordinary speech acts, like predictions or retractions. Secondly, I indicate how the normative view can be extended to so-called ancillary speech acts, like presuppositions or implicatures. I end with a discussion of possible extensions of the normative approach, focusing on the debate on lying.</p

Contributions to information extraction for spanish written biomedical text

285 p.Healthcare practice and clinical research produce vast amounts of digitised, unstructured data in multiple languages that are currently underexploited, despite their potential applications in improving healthcare experiences, supporting trainee education, or enabling biomedical research, for example. To automatically transform those contents into relevant, structured information, advanced Natural Language Processing (NLP) mechanisms are required. In NLP, this task is known as Information Extraction. Our work takes place within this growing field of clinical NLP for the Spanish language, as we tackle three distinct problems. First, we compare several supervised machine learning approaches to the problem of sensitive data detection and classification. Specifically, we study the different approaches and their transferability in two corpora, one synthetic and the other authentic. Second, we present and evaluate UMLSmapper, a knowledge-intensive system for biomedical term identification based on the UMLS Metathesaurus. This system recognises and codifies terms without relying on annotated data nor external Named Entity Recognition tools. Although technically naive, it performs on par with more evolved systems, and does not exhibit a considerable deviation from other approaches that rely on oracle terms. Finally, we present and exploit a new corpus of real health records manually annotated with negation and uncertainty information: NUBes. This corpus is the basis for two sets of experiments, one on cue andscope detection, and the other on assertion classification. Throughout the thesis, we apply and compare techniques of varying levels of sophistication and novelty, which reflects the rapid advancement of the field

Rule-based approach for identifying assertions in clinical free-text data

A rule-based approach for classifying previously identified medical concepts in the clinical free text into an assertion category is presented. There are six different categories of assertions for the task: Present, Absent, Possible, Conditional, Hypothetical and Not associated with the patient. The assertion classification algorithms were largely based on extending the popular NegEx and Context algorithms. In addition, a health based clinical terminology called SNOMED CT and other publicly available dictionaries were used to classify assertions, which did not fit the NegEx/Context model. The data for this task includes discharge summaries from Partners HealthCare and from Beth Israel Deaconess Medical Centre, as well as discharge summaries and progress notes from University of Pittsburgh Medical Centre. The set consists of 349 discharge reports, each with pairs of ground truth concept and assertion files for system development, and 477 reports for evaluation. The system’s performance on the evaluation data set was 0.83, 0.83 and 0.83 for recall, precision and F1-measure, respectively. Although the rule-based system shows promise, further improvements can be made by incorporating machine learning approaches

Norms of Speech Acts

This paper offers a systematic classification and characterization of speech acts and their norms. Recently, the normative approach has been applied to various speech acts, most notably to constatives. I start by showing how the work on the norms of assertion has influenced various approaches to the norms of other speech acts. I focus on the fact that various norms of assertion have different extensions, i.e., they denote different clusters of illocutions as belonging to an assertion. I argue that this has consequences for theorising about norms of other speech acts and generates certain arbitrary divisions. In the central part, I analyse two groups of speech acts. Firstly, ordinary speech acts, like predictions or retractions. Secondly, I indicate how the normative view can be extended to so-called ancillary speech acts, like presuppositions or implicatures. I end with a discussion of possible extensions of the normative approach, focusing on the debate on lying

Emergence of computing education as a research discipline

This thesis investigates the changing nature and status of computing education research (CER) over a number of years, specifically addressing the question of whether computing education can legitimately be considered a research discipline. The principal approach to addressing this question is an examination of the published literature in computing education conferences and journals. A classification system was devised for this literature, one goal of the system being to clearly identify some publications as research – once a suitable definition of research was established. When the system is applied to a corpus of publications, it becomes possible to determine the proportion of those publications that are classified as research, and thence to detect trends over time and similarities and differences between publication venues. The classification system has been applied to all of the papers over several years in a number of major computing education conferences and journals. Much of the classification was done by the author alone, and the remainder by a team that he formed in order to assess the inter-rater reliability of the classification system. This classification work led to two subsequent projects, led by Associate Professor Judy Sheard and Professor Lauri Malmi, that devised and applied further classification systems to examine the research approaches and methods used in the work reported in computing education publications. Classification of nearly 2000 publications over ranges of 3-10 years uncovers both strong similarities and distinct differences between publication venues. It also establishes clear evidence of a substantial growth in the proportion of research papers over the years in question. These findings are considered in the light of published perspectives on what constitutes a discipline of research, and lead to a confident assertion that computing education can now rightly be considered a discipline of research