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Tech Report kmi-99-01 Abstract


Collaborative Sense-Making in Design: Involving Stakeholders via Representational Morphing
Techreport ID: kmi-99-01
Date: 1999
Author(s): Simon J. Buckingham Shum and Albert M. Selvin*
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A central concern in CSCW research is to understand, and represent, the perspectives of the different stakeholders in the design process. This paper suggests collaborative sense-making as a way to view the process toward creating mutually intelligible representations. In order to do this, we describe the types of obstacles that can impede representational literacy across communities of practice coming together in a design effort. We then offer representational morphing as a strategy for addressing these obstacles, and show how it has been implemented in an approach and hypermedia groupware environment named Project Compendium. We conclude by reflecting on the key features of the approach and collaborative tool support which have contributed to this project1s success to date. * Bell Atlantic Corporation Network Systems Advanced Technology 400 Westchester Avenue White Plains, NY 10604 U.S.A.
 
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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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