Abstract
Traditional news media report a single set of articles on cur- rent news stories. Online news sources make multiple stories on the same topic available reflecting different perspectives on the same news event. Navigating between these news sources to find stories of interest can be time consuming and inefficient. These multiple stories can be combined into personalised news packages by selecting items on topics of interest to an individual user. The appropriate contents of these personalised news packages can be determined by a combination of information retrieval techniques and explicit user preferences. This paper describes systems exploring this approach to personalised news delivery.
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
M. F. Porter. An algorithm for suffix stripping. Program, 14(3):130–137, July 1980.
K. Spärck Jones, S. Walker, and S. E. Robertson. A probabilistic model of information retrieval: development and status. Technical Report 446, Cambridge University Computer Laboratory, August 1998.
N. Uramoto and K. Takeda. A method for relating multiple newspaper articles by using graphs, and its application to webcasting. In Proceedings of COLING 98, pages 1307–1313, Montreal, 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jones, G.J.F., Quested, D.J., Thomson, K.E. (2000). Personalised Delivery of News Articles from Multiple Sources. In: Borbinha, J., Baker, T. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2000. Lecture Notes in Computer Science, vol 1923. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45268-0_35
Download citation
DOI: https://doi.org/10.1007/3-540-45268-0_35
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-41023-2
Online ISBN: 978-3-540-45268-3
eBook Packages: Springer Book Archive