Tech Reports
Tech Report kmi-01-13 Abstract
Cognitive Coherence Relations and Hypertext: From Cinematic Patterns to Scholarly Discourse
Techreport ID: kmi-01-13
Date: 2001
Author(s): Clara Mancini and Simon Buckingham Shum
In previous work we argued that cinematic language may provide insights into the construction of narrative coherence in hypertext, and we identified in the shot juxtaposition of rhetorical patterns the source of coherence for cinematic discourse. Here we deepen our analysis, to show how the mechanisms that underpin cinematic rhetorical patterns are the same as those providing coherence in written text. We draw on computational and psycholinguistic analyses of texts which have derived a set of relationships that are termed Cognitive Coherence Relations (CCR). We validate this by re-expressing established cinematic patterns, and relations relevant to scholarly hypertext, in terms of CCR, and with this conceptual bridge in place, present examples to show how cinematic techniques could assist the presentation of scholarly discourse. This theoretical work also informs system design. We describe how an abstract relational layer based on CCR is being implemented as a semantic hypertext system to mediate scholarly discourse.
Publication(s):
Proceedings of ACM Hypertext 2001, Aarhus, Denmark, August 2001 [http://www.HT01.org]
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Multimedia and Information Systems is...

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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