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Tech Report kmi-05-10 Abstract


The Modelling, Capture, and Use of Social Context in Online Tasks
Techreport ID: kmi-05-10
Date: 2005
Author(s): Tom Heath
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This report consists of three parts. Part I reviews how users online tasks have been conceptualised in previous literature, and how researchers have defined and used context in support of user tasks. Novel conceptualisations of user tasks online and user context factors are then presented and contrasted with earlier work, before a discussion of how these context factors have been supported in previous applications. The modelling of social context is then considered in greater detail, with particular focus on aspects such as the nature of social relationships and trust between individuals. Research gaps identified through this review of the literature are summarised to conclude this section. Part II addresses specific outputs of the research to date. In particular, the conceptualisations of user tasks online and user contexts are discussed in more detail, including coverage of the assumptions they are based upon and the background to their development. Specific technical work carried out is also described, including the planning of a social context application, analysis of tools and technologies that may be utilised, and development of relevant technical skills. Drawing on the gaps identified in Part I of the report, Part III introduces the questions that will be addressed by the research. After justifying the research questions, the methods that will be used are outlined and discussed, including overall plans for how the research will be carried out.
 
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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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