Abstract
In this paper we propose an incremental hierarchical clustering algorithm for on-line event detection. This algorithm is applied to a set of newspaper articles in order to discover the structure of topics and events that they describe. In the first level, articles with a high temporal-semantic similarity are clustered together into events. In the next levels of the hierarchy, these events are successively clustered so that composite events and topics can be discovered. The results obtained for the F1-measure and the Detection Cost demonstrate the validity of our algorithm for on-line event detection tasks.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Allan, J.; Lavrenko, V.; Frey, D.; Khandelwal, V.: UMass at TDT 2000. In Proc. TDT 2000 Workshop, 2000.
Larsen, B.; Aone, C.: Fast and Effective Text Mining Using Linear-time Document Clustering. In KDD’99, San Diego, California, pp. 16–22, 1999.
Llidó, D.; Berlanga R.; Aramburu M.J.: Extracting temporal references to automatically assign document event-time periods. In Proc. Database and Expert System Applications 2001, 62–71, Springer-Verlag, Munich, 2001.
National Institute of Standards and Technology. The Topic Detection and Tracking Phase 2 (TDT2) evaluation plan. version 3.7, 1998.
Papka, R.: On-line New Event Detection, Clustering and Tracking. Ph.D. Thesis Report, University of Massachusetts, Department of Computer Science, 1999.
Pons-Porrata, A.; Berlanga-Llavori, R.; Ruiz-Shulcloper, J.: Detecting events and topics by using temporal references. Lecture Notes in Artificial Intelligence 2527, Springer Verlag, 2002, pp.11–20.
Ruiz-Shulcloper, J.; Sánchez Díaz, G.; Abidi, M.A.: Heuristics & Optimization for Knowledge Discovery, Chapter VI. Clustering in mixed incomplete data, Editors H.A. Abbass, R.A. Sarker, C.S. Newton, Idea Group Publishing, USA. pp 88–106. January 2002.
Swan R. C.; Allan, J.: Automatic generation of overview timelines. In Proc. ACM/SIGIR 2000, pp. 49–56, 2000.
Yang, Y.; Pierce, T.; Carbonell, J.: A Study of Retrospective and On-Line Event Detection. In Proc. ACM/SIGIR 1998, pp. 28–36, 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pons-Porrata, A., Berlanga-Llavori, R., Ruiz-Shulcloper, J. (2003). Building a Hierarchy of Events and Topics for Newspaper Digital Libraries. In: Sebastiani, F. (eds) Advances in Information Retrieval. ECIR 2003. Lecture Notes in Computer Science, vol 2633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36618-0_46
Download citation
DOI: https://doi.org/10.1007/3-540-36618-0_46
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-01274-0
Online ISBN: 978-3-540-36618-8
eBook Packages: Springer Book Archive