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Tech Report kmi-01-15 Abstract


Facilitated Hypertext for Collective Sensemaking: 15 Years on from gIBIS
Techreport ID: kmi-01-15
Date: 2001
Author(s): Jeff Conklin, Albert Selvin, Simon Buckingham Shum and Maarten Sierhuis
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Hypertext research in the mid-1980s on representing argumentation for design rationale (DR) foreshadowed what are now dominant concerns in knowledge management: representing, codifying and manipulating semiformal concepts, the use of formalisms to mediate collective sensemaking, and the construction of group memory. With the benefit of 15 years' hindsight, we can see the failure of so many hypertext DR systems to be adopted as symptomatic of the more general problem of fostering 'hypertext literacy' in real working environments. Pursuing Englebart's goal of "augmenting human intellect", we describe the Compendium approach to collective sensemaking, which demonstrates the impact that a hypertext facilitator can have on the learning and adoption problems that plagued earlier hypertext systems. We also describe how conventional documents and modelling notations can be morphed into and out of Compendium's 'native hypertext' in order to support other modes of working across diverse communities of practice. Keywords: facilitation, collaborative hypertext, formalism, sensemaking, knowledge management, argumentation, IBIS
 
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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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