Tech Reports
Tech Report kmi-04-02 Abstract
Nootropia: a Self-Organising Agent for Adaptive Document Filtering
Techreport ID: kmi-04-02
Date: 2004
Author(s): Nikolaos Nanas, Victoria Uren, Anne de Roeck, John Domingue
This paper presents Nootropia, a self-organising information agent, capable of evaluating documents according to a user's multiple and changing interests. In Nootropia, a hierarchical term network that takes into account term dependencies is used to represent a user's multiple topics of interest. Non-linear document evaluation is established on that network based on a directed spreading activation model. We then introduce a process for adjusting the network in response to changes in user feedback. We argue that Nootropia exhibits self-organising characteristics, which, as demonstrated experimentally, allow Nootropia to adapt to a variety of simulated interest changes.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Social Software is...
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.
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