Acquiring and Using Limited User Models in NLG

It is a truism of NLG that good knowledge of the reader can improve the quality of generated texts, and many NLG systems have been developed that exploit detailed user models when generating texts. Unfortunately, it is very difficult in practice to obtain detailed information about users. In this paper we describe our experiences in acquiring and using limited user models for NLG in four different systems, each of which took a different approach to this issue. One general conclusion is that it is useful if imperfect user models are understandable to users or domain experts, and indeed perhaps can be directly edited by them; this agrees with recent thinking about user models in other applications such as intelligent tutoring systems (Kay, 2001)

Machine learning research 1989-90

Multifunctional knowledge bases offer a significant advance in artificial intelligence because they can support numerous expert tasks within a domain. As a result they amortize the costs of building a knowledge base over multiple expert systems and they reduce the brittleness of each system. Due to the inevitable size and complexity of multifunctional knowledge bases, their construction and maintenance require knowledge engineering and acquisition tools that can automatically identify interactions between new and existing knowledge. Furthermore, their use requires software for accessing those portions of the knowledge base that coherently answer questions. Considerable progress was made in developing software for building and accessing multifunctional knowledge bases. A language was developed for representing knowledge, along with software tools for editing and displaying knowledge, a machine learning program for integrating new information into existing knowledge, and a question answering system for accessing the knowledge base

Recommender systems and their ethical challenges

This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of concern, and maps them onto a proposed taxonomy of different kinds of ethical impact. The analysis uncovers a gap in the literature: currently user-centred approaches do not consider the interests of a variety of other stakeholders—as opposed to just the receivers of a recommendation—in assessing the ethical impacts of a recommender system

Interactive Multimedia Explanation for Equipment Maintenance and Repair

COMET (COordinated Multimedia Explanation Testbed) is a research system that we are developing to explore the coordinated generation of multimedia explanations of equipment maintenance and repair procedures. The form and content of all material presented is generated interactively, with an emphasis on coordinating multiple media to allow cross-references between media and to make possible display layout that reflects the fine-grain relationships among the material presented. COMET's architecture includes multiple static and dynamic knowledge sources, a content planner, a media coordinator, media generators (currently text and graphics), and a media layout manager. Examples are given of the kinds of material processed and produced by each of the components

Using XML-based Metadata for Generating Dynamic Courseware

The objective of this paper is to explore the mechanism between the learner and learning material in generating dynamic courseware in e-learning environment, The dynamic e-learning develop flexible and dynamic course content according to the suitability level of learner, This dynamic e-learning will be using XML-based metadata in particular. XML based metadata allows any part of a course to be modularized, saves and reused as a learning object. Each learning object is described in the object repository. Learning objects are stored in central object repository and are easily locatable on an object-by-object basis. To achieve learner adaptability, learners are allowed to specify queries that will dynamically construct courses

The added value of implementing the Planet Game scenario with Collage and Gridcole

This paper discusses the suitability and the added value of Collage and Gridcole when contrasted with other solutions participating in the ICALT 2006 workshop titled “Comparing educational modelling languages on a case study.” In this workshop each proposed solution was challenged to implement a Computer-Supported Collaborative Learning situation (CSCL) posed by the workshop’s organizers. Collage is a pattern-based authoring tool for the creation of CSCL scripts compliant with IMS Learning Design (IMS LD). These IMS LD scripts can be enacted by the Gridcole tailorable CSCL system. The analysis presented in the paper is organized as a case study which considers the data recorded in the workshop discussion as well the information reported in the workshop contributions. The results of this analysis show how Collage and Gridcole succeed in implementing the scenario and also point out some significant advantages in terms of design reusability and generality, user-friendliness, and enactment flexibility

Coordinating Text and Graphics in Explanation Generation

To generate multimedia explanations, a system must be able to coordinate the use of different media in a single explanation. In this paper, we present an architecture that we have developed for COMET (COordinated Multimedia Explanation Testbed), a system that generates directions for equipment maintenance and repair, and we show how it addresses the coordination problem. In particular, we focus on the use of a single content planner that produces a common content description used by multiple media-specific generators, a media coordinator that makes a f'me-grained division of information between media, and bidirectional interaction between media-specific generators to allow influence across media.