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Tech Report kmi-01-17 Abstract


Research Proposal: An Adaptive, Evolutionary User Profile for Knowledge Management.
Techreport ID: kmi-01-17
Date: 2001
Author(s): Nikolaos Nanas
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In order to provide the knowledge worker with potentially useful information, we propose an architecture for the development of an adaptive, evolutionary user profile. The profile has the ability to adapt to modest, frequent changes to the individual's information needs and in addition to evolve, in order to adjust to more radical but less frequent changes. In order to descrive the architecture, we discuss the profile's initialization, its evolutionary mechanism, the way it evaluates documents and the way it is adapted. Furthermore, we present a number of knowledge management services and the way that they can be realized based on the proposed architecture. We conclude by enumerating the different stages of the system's development and the corresponding experimentation and testing that will take place at its stage. Keywords: Knowledge management, user profiling, associative networks, adaptation, evolution.
 
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Social Software is...


Social Software
Social Software can be thought of as "software which extends, or derives added value from, human social behaviour - message boards, musical taste-sharing, photo-sharing, instant messaging, mailing lists, social networking."

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.