KMi Seminars
Building Collaborative Knowledge Representations in Real Time
This event took place on Tuesday 05 October 2004 at 12:30

 
Al Selvin

Software tools for collaborative construction of knowledge representations have existed for several decades. Despite their potential, use of such tools has yet to grow beyond a small universe of academics and practitioners. My research is aimed at expanding this universe by attempting to understand and characterize skilled practice in the facilitation of such representations. Most of the limited work in this area looks at either novices (e.g., learning how to construct such representations), on outcome measures such as participant satisfaction, or on the characteristics of the knowledge artifacts and technologies themselves. I am focusing instead on the "high end" of skilled or expert practice. To do this, I am closely analyzing Camtasia recordings of Compendium sessions and attempting to build a grounded theory analysis of practitioner (facilitator) "moves" in the context of the sessions. This talk reports on the first of these analyses, of a 137-minute Webex and teleconference Compendium session held with a team of scientists participating in the NASA Mobile Agents field trial in May 2004. I analyze 761 facilitator statements and Compendium moves, which were categorized in such terms as degree and kind of engagement, areas of focus, type of move, and other criteria.

Download PowerPoint Presentation (5Mb ZIP file)
Spreadsheet referenced in talk (HTML copy)
Mobile Agents Movie Clip (7.4Mb QuickTime 6 file)

 
KMi Seminars 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.

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