Algorithms 2012, 5(3), 364-378; doi:10.3390/a5030364
Article

Incremental Clustering of News Reports

Joel Azzopardi* email and Christopher Staff
Faculty of ICT, University of Malta, Msida, MSD2080, Malta
* Author to whom correspondence should be addressed.
Received: 29 June 2012; in revised form: 13 August 2012 / Accepted: 15 August 2012 / Published: 24 August 2012
(This article belongs to the Special Issue Selected Papers from Text Mining Workshop at the 2012 SIAM International Conference on Data Mining)
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Abstract: When an event occurs in the real world, numerous news reports describing this event start to appear on different news sites within a few minutes of the event occurrence. This may result in a huge amount of information for users, and automated processes may be required to help manage this information. In this paper, we describe a clustering system that can cluster news reports from disparate sources into event-centric clusters—i.e., clusters of news reports describing the same event. A user can identify any RSS feed as a source of news he/she would like to receive and our clustering system can cluster reports received from the separate RSS feeds as they arrive without knowing the number of clusters in advance. Our clustering system was designed to function well in an online incremental environment. In evaluating our system, we found that our system is very good in performing fine-grained clustering, but performs rather poorly when performing coarser-grained clustering.
Keywords: clustering; news; event detection; incremental clustering

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Cite This Article

MDPI and ACS Style

Azzopardi, J.; Staff, C. Incremental Clustering of News Reports. Algorithms 2012, 5, 364-378.

AMA Style

Azzopardi J, Staff C. Incremental Clustering of News Reports. Algorithms. 2012; 5(3):364-378.

Chicago/Turabian Style

Azzopardi, Joel; Staff, Christopher. 2012. "Incremental Clustering of News Reports." Algorithms 5, no. 3: 364-378.

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