KMi Seminars
The role of layout in natural language processing (NLP)
This event took place on Monday 01 November 2004 at 12:45

 
Prof. Donia Scott Centre for Research in Computing, The Open University, UK

This talk will present the case for abstract document structure as a separate descriptive level in the analysis and generation of written texts. The purpose of this representation is to mediate between the message of a text (i.e., its discourse structure) and its physical presentation (i.e., its organisation into graphical constituents like sections, paragraphs, sentences, bulleted lists, figures, footnotes and so forth). Abstract document structure can be seen as an extension of Nunberg's `text-grammar'; it is also closely related to `logical' mark-up in languages like HTML and LaTeX. I will argue that by using this intermediate representation, several subtasks in language generation and language understanding can be defined more cleanly.

Biography

Donia Scott is professor of Computational Linguistics at the University of Brighton, where she has been director of the Information Technology Research Institute since 1991. During this period she has built a research group specializing in several areas of computational linguistics, especially natural language generation (NLG), lexical representation, and corpus linguistics. Her own research has focused on multilingual NLG, and on the realization of rhetorical relationships through layout, punctuation, and discourse connectives. Earlier in her career Professor Scott worked for some years on speech and intonation, at Sussex University and Philips Research Laboratories.

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KMi Seminars Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

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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