Towards Nootropia: a Non-Linear Approach to Adaptive Document Filtering
This event took place on Monday 02 February 2004 at 12:30
Nikolaos Nanas
In recent years, it has become increasingly difficult for users to find relevant information within the accessible glut. Adaptive Information Filtering (AIF) tackles this problem through a tailored representation of the user interests, called "user profile". The user profile must be able to represent the user's multiple topics of interest and adapt to various changes in them.
With our experimental system 'Nootropia', we achieve adaptive document filtering with a single, multi-topic user profile. A hierarchical term network that takes into account topical and lexical correlations between terms and identifies topic-subtopic relations between them, is used to represent a user's multiple interests and distinguish between them. A series of non-linear document evaluation functions is then established on the hierarchical network. Adaptation is then achieved through a process of self-organisation that constantly readjusts the profile stucturally, in response to user feedback. The approach has been tested experimentally with positive results. Furthemore, Nootropia may support additional personalisation services like automatic query formulation and expert finding, or can be applied in combination with collaborative filtering. It is also interesting that, in principle, the approach can be applied to other media like audio and image for which features can be automatically extracted.
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This event took place on Monday 02 February 2004 at 12:30
In recent years, it has become increasingly difficult for users to find relevant information within the accessible glut. Adaptive Information Filtering (AIF) tackles this problem through a tailored representation of the user interests, called "user profile". The user profile must be able to represent the user's multiple topics of interest and adapt to various changes in them.
With our experimental system 'Nootropia', we achieve adaptive document filtering with a single, multi-topic user profile. A hierarchical term network that takes into account topical and lexical correlations between terms and identifies topic-subtopic relations between them, is used to represent a user's multiple interests and distinguish between them. A series of non-linear document evaluation functions is then established on the hierarchical network. Adaptation is then achieved through a process of self-organisation that constantly readjusts the profile stucturally, in response to user feedback. The approach has been tested experimentally with positive results. Furthemore, Nootropia may support additional personalisation services like automatic query formulation and expert finding, or can be applied in combination with collaborative filtering. It is also interesting that, in principle, the approach can be applied to other media like audio and image for which features can be automatically extracted.
Download PowerPoint Presentation (1Mb ZIP file)
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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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