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Multi-topic information filtering with a single user profile

Nanas, Nikolaos; Uren, Victoria; De Roeck, Anne and Domingue, John (2004). Multi-topic information filtering with a single user profile. In: 3rd Hellenic Conference on Artificial Intelligence (SETN 04), 5-8 May 2004, Pythagorion, Samos, Greece, Springer, pp. 400–409.

DOI (Digital Object Identifier) Link: http://dx.doi.org/10.1007/b97168
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Abstract

In Information Filtering (IF) a user may be interested in several topics in parallel. But IF systems have been built on representational models derived from Information Retrieval and Text Categorization, which assume independence between terms. The linearity of these models results in user profiles that can only represent one topic of interest. We present a methodology that takes into account term dependencies to construct a single profile representation for multiple topics, in the form of a hierarchical term network. We also introduce a series of non-linear functions for evaluating documents against the profile. Initial experiments produced positive results.

Item Type: Conference Item
Copyright Holders: 2004 Springer
ISBN: 3-540-21937-4, 978-3-540-21937-8
ISSN: 0302-9743
Academic Unit/Department: Mathematics, Computing and Technology > Computing & Communications
Knowledge Media Institute
Mathematics, Computing and Technology
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 19291
Depositing User: Colin Smith
Date Deposited: 22 Dec 2009 12:02
Last Modified: 29 Sep 2011 10:12
URI: http://oro.open.ac.uk/id/eprint/19291
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