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
Multimedia and Information Systems is...
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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