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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: Methods and Applications of Artificial Intelligence (Vouros, George A. and Panayiotopoulos, Themistoklis eds.), Lecture Notes in Computer Science, Springer, Berlin, pp. 400–409.

DOI (Digital Object Identifier) Link: http://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
Mathematics, Computing and Technology
Knowledge Media Institute
Other Departments > Vice-Chancellor's Office
Other Departments
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: 22 Mar 2016 16:48
URI: http://oro.open.ac.uk/id/eprint/19291
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