25 research outputs found
Generating Coherent Messages in Real-time Decision Support: Exploiting Discourse Theory for Discourse Practice
This paper presents a message planner, TraumaGEN, that draws on rhetorical
structure and discourse theory to address the problem of producing integrated
messages from individual critiques, each of which is designed to achieve its
own communicative goal. TraumaGEN takes into account the purpose of the
messages, the situation in which the messages will be received, and the social
role of the system.Comment: 6 page
Authoring and generation of individualized patient education materials
ABSTRACT Although the pre-surgical patient-surgeon encounter is the opportunity to educate the patient, it is essential that the patient be given educational materials to complement the face-to-face exchange. This is virtually impossible to do well with brochures, because many combinations of procedures are possible, different patients have different concerns, and patients have varying levels of literacy and knowledge. In the extreme, a patient would either be given a set of brochures selected from 100s of variants, or all patients would be given the same set of brochures without regard for differing needs. We have been developing an information brochure generator that customizes material for every individual patient regardless of the complexity of the surgical intervention
Summarisation and visualisation of e-Health data repositories
At the centre of the Clinical e-Science Framework (CLEF) project is a repository of well organised,
detailed clinical histories, encoded as data that will be available for use in clinical care and in-silico
medical experiments. We describe a system that we have developed as part of the CLEF project, to perform the task of generating a diverse range of textual and graphical summaries of a patient’s clinical history from a data-encoded model, a chronicle, representing the record of the patient’s medical history. Although the focus of our current work is on cancer patients, the approach we
describe is generalisable to a wide range of medical areas
A Reference Architecture for Natural Language Generation Systems
We present the RAGS (Reference Architecture for Generation Systems) framework: a specification of an abstract Natural Language Generation (NLG) system architecture to support sharing, re-use, comparison and evaluation of NLG technologies. We argue that the evidence from a survey of actual NLG systems calls for a different emphasis in a reference proposal from that seen in similar initiatives in information extraction and multimedia interfaces.
We introduce the framework itself, in particular the two-level data model that allows us to support the complex data requirements of NLG systems in a flexible and coherent fashion, and describe our efforts to validate the framework through a range of implementations
Implementation architectures for natural language generation
Generic software architectures aim to support re-use of components, focusing of research and development effort, and evaluation and comparison of approaches. In the field of natural language processing, generic frameworks for understanding have been successfully deployed to meet all of these aims, but nothing comparable yet exists for generation. The nature of the task itself, and the current methodologies available to research it, seem to make it more difficult to reach the necessary level of consensus to support generic proposals. Recent work has made progress towards establishing a generic framework for generation at the functional level, but left open the issue of actual implementation. In this paper, we discuss the requirements for such an implementation layer for generation systems, drawing on two initial attempts to implement it. We argue that it is possible and useful to distinguish “functional architecture ” from “implementation architecture” for generation systems. 1 The Case for a Generic Software Architecture for NLG Most natural language generation (NLG) systems have some kind of modular structure
IMPACTS in natural language generation NLG between technology and applications : workshop at Schloss Dagstuhl, Germany July 26-28, 2000
Instructional text, because it is a useful and relatively constrained sub-Ianguage, has been a popular target for research-oriented generation systems. This work has demonstrated that existing technology is adequate for generating draft instructions; the problem, as is typical of generation work in general, has been with the acquisition of domain and lexicogrammatical knowledge. This acquisition task is a formidable barrier to the practical use of generation
technology. The Isolde project attempts to address this problem by extracting
parts of the required knowledge from existing models and by building tools to
tailor what is extracted into a form suitable for generation