Towards Nootropia: a Non-Linear Approach to Adaptive Document Filtering Nikolaos Nanas Knowledge Media Institute 8 December 2003 Supervisors: Dr Victoria S. Uren, Professor Anne De Roeck and Dr John Domingue In recent years, it has become increasingly di cult for users to nd relevant information within the accessible glut. Research in Information Filtering (IF) tackles this problem through a tailored representation of the user interests, a user pro le. Traditionally, IF inherits techniques from the related and more well established domains of Information Retrieval and Text Categorisation. These include, linear pro le representations that exclude term dependencies and may only represent a single topic of interest, and linear learning algorithms that achieve a steady pro le adaptation pace. We argue that these practices are not attuned to the dynamic nature of user interests. A user may be interested in more than one topic in parallel, and both frequent variations and occasional radical changes of interests are inevitable over time. With our experimental system Nootropia , we achieve adaptive document ltering with a single, multi-topic user pro le. A hierarchical term network that takes into account topical and lexical correlations between terms and identi es topic-subtopic relations between them, is used to represent a user s multiple topics of interest and distinguish between them. A series of non-linear document evaluation functions is then established on the hierarchical network. Experiments using a variation of TREC s routing subtask to test the ability of a single pro le to represent two and three topics of interest, reveal the approach s superiority over a linear pro le representation. Adaptation of this single, multi-topic pro le to a variety of changes in the user interests, is then achieved through a process of self-organisation that constantly readjusts the pro le stucturally, in response to user feedback. We used virtual users and another variation of TREC s routing subtask to test the pro le on two learning and two forgetting tasks. The results clearly indicate the pro le s ability to adapt to both frequent variations and radical changes in user interests. ACM SIGIR Forum Vol. 38 No. 1 June 2004
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Towards Nootropia: a non-linear approach to adaptive document filtering
Nanas, Nikolaos
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, Volume 38 (1)
Association for Computing Machinery – Jul 1, 2004
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