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Tech Report KMI-06-07 Abstract


Co-OPR: Design and Evaluation of Collaborative Sensemaking and Planning Tools for Personnel Recovery
Techreport ID: KMI-06-07
Date: 2006
Author(s): Austin Tate, Simon Buckingham Shum, Jeff Dalton, Clara Mancini, Albert Selvin
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Personnel recovery teams must operate under intense pressure, taking into account not only hard logistics, but 'messy' factors such as the social or political implications of a decision. The Collaborative Operations for Personnel Recovery (Co-OPR) project has developed decision-support for sensemaking in such scenarios, seeking to exploit the complementary strengths of human and machine reasoning. Co-OPR integrates the Compendium sensemaking-support tool for real time information and argument mapping, with the I-X artificial intelligence planning and execution framework to support group activity and collaboration. Both share a common model for dealing with issues, the refinement of options for the activities to be performed, handling constraints and recording other information. The tools span the spectrum from being very flexible with few constraints on terminology and content, to knowledge-based relying on rich domain models and formal conceptual models (ontologies). In a personnel recovery experimental simulation of an UN peacekeeping operation, with roles played by military planning staff, the Co-OPR tools were judged by external evaluators to have been very effective.
 
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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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