KMi Publications

Tech Reports

Tech Report KMI-06-14 Abstract


Modelling Discourse in Contested Domains: A Semiotic and Cognitive Framework
Techreport ID: KMI-06-14
Date: 2006
Author(s): Clara Mancini, Simon Buckingham Shum
Download PDF

This paper examines the representational requirements for interactive, collaborative systems intended to support sensemaking and argumentation over contested issues. We argue that a perspective supported by semiotic and cognitively oriented discourse analyses offers both theoretical insights and motivates representational requirements for the semantics of tools for contesting meaning. We introduce our semiotic approach, highlighting its implications for discourse representation, before describing a research system (ClaiMaker) designed to support the construction of scholarly argumentation by allowing analysts to publish and contest 'claims' about scientific contributions. We show how ClaiMaker's representational scheme is grounded in specific assumptions concerning the nature of explicit modelling, and the evolution of meaning within a discourse community. These characteristics allow the system to represent scholarly discourse as a dynamic process, in the form of continuously evolving structures. A cognitively oriented discourse analysis then shows how the use of a small set of cognitive relational primitives in the underlying ontology opens possibilities for offering users advanced forms of computational service for analysing collectively constructed argumentation networks.

Publication(s):

Mancini, C. and Buckingham Shum, S.J. (In Press). Modelling Discourse in Contested Do-mains: A Semiotic and Cognitive Framework. International Journal of Human Computer Studies. [PrePrint: http://kmi.open.ac.uk/publications/pdf/KMI-TR-06-14.pdf]
 
KMi Publications 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.

Visit the MMIS website