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Tech Report KMI-06-19 Abstract


Visualising Discourse Coherence in Non-Linear Documents
Techreport ID: KMI-06-19
Date: 2006
Author(s): Clara Mancini, Donia Scott and Simon Buckingham Shum
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To produce coherent linear documents, Natural Language Generation systems have traditionally exploited the structuring role of textual discourse markers such as relational and referential phrases. These coherence markers of the traditional notion of text, however, do not work in non-linear documents: a new set of graphical devices is needed together with formation rules to govern their usage, supported by sound theoretical frameworks. If in linear documents graphical devices such as layout and formatting complement textual devices in the expression of discourse coherence, in non-linear documents they play a more important role. In this paper, we present our theoretical and empirical work in progress, which explores new possibilities for expressing coherence in the generation of hypertext documents.

Publication(s):

Mancini, C., Scott, D. and Buckingham Shum, S.J. (2006). Visualising Discourse Coherence in Non-Linear Documents. Traitement Automatique des Langues, (Special Issue on Computational Approaches to Document and Discourse, Eds. Marie-Paule Péry-Woodley & Donia Scott), 47, (1). PrePrint available as: http://kmi.open.ac.uk/publications/pdf/KMI-TR-06-19.pdf
 
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Multimedia and Information Systems is...


Multimedia and Information Systems
Our research is centred around the theme of Multimedia Information Retrieval, ie, Video Search Engines, Image Databases, Spoken Document Retrieval, Music Retrieval, Query Languages and Query Mediation.

We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.

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