Abstract
In this paper, we propose an event words based method for story link detection. Different from previous studies, we use time and places to label nouns and named entities, the featured nouns/named entities are called event words. In our approach, a document is represented by five dimensions including nouns/named entities, time featured nouns/named entities, place featured nouns/named entities, time&place featured nouns/named entities and publication date. Experimental results show that, our method gain a significant improvement over baseline and event words plays a vital role in this improvement. Especially when using publication date, we can reach the highest 92% on precision.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Allan, J.: Topic detection and tracking: event-based information organization. Kluwer Academic Publishers, Norwell (2002)
Allan, J., Lavrenko, V., Swan, R.: Explorations within topic tracking and detection, pp. 197–224 (2002)
Brown, R.D.: Dynamic stopwording for story link detection. In: Proceedings of the Second International Conference on Human Language Technology Research, pp. 190–193. Morgan Kaufmann Publishers Inc., San Francisco (2002)
Chen, F., Farahat, A., Brants, T.: Story link detection and new event detection are asymmetric. In: NAACL 2003: Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology, pp. 13–15. Association for Computational Linguistics, Morristown (2003), doi:10.3115/1073483.1073488
Chen, F., Farahat, A., Brants, T.: Multiple similarity measures and source-pair information in story link detection. In: In HLT-NAACL 2004, pp. 2–7 (2004)
Chen, Y.-J., Chen, H.-H.: Nlp and ir approaches to monolingual and multilingual link detection. In: Proceedings of the 19th International Conference on Computational Linguistics, pp. 1–7. Association for Computational Linguistics, Morristown (2002)
Farahat, A., Chen, F., Brants, T.: Optimizing story link detection is not equivalent to optimizing new event detection. In: ACL 2003: Proceedings of the 41st Annual Meeting on Association for Computational Linguistics, pp. 232–239. Association for Computational Linguistics, Morristown (2003)
Ferret, O.: Using collocations for topic segmentation and link detection. In: Proceedings of the 19th International Conference on Computational Linguistics, pp. 1–7. Association for Computational Linguistics, Morristown (2002)
Hong, Y., Zhang, Y., Fan, J., Liu, T., Li, S.: Chinese topic link detection based on semantic domain language model. Journal of Software, 2265–2275 (2008)
Lavrenko, V., Allan, J., DeGuzman, E., LaFlamme, D., Pollard, V., Thomas, S.: Relevance models for topic detection and tracking. In: Proceedings of the Second International Conference on Human Language Technology Research, pp. 115–121. Morgan Kaufmann Publishers Inc., San Francisco (2002)
Luo, W., Liu, Q., Chen, X.: Development and analysis of technology of topic detection and tracking. In: Sun, M.S. (ed.) Proc. of the JSCL 2003, Beijing, China, pp. 560–566 (2003)
Nallapati, R.: Semantic language models for topic detection and tracking. In: NAACL 2003: Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology, Edmonton, Canada, pp. 1–6. Association for Computational Linguistics, Morristown (2003)
Schultz, J.M., Liberman, M.Y.: Towards a “universal dictionary” for multi-language information retrieval applications, pp. 225–241 (2002)
Shah, C., Croft, W.B., Jensen, D.: Representing documents with named entities for story link detection (sld). In: CIKM 2006: Proceedings of the 15th ACM International Conference on Information and Knowledge Management, pp. 868–869. ACM, New York (2006)
Wayen, C.L.: Multilingual topic detection and tracking: Successful research enabled by corpora and evaluation. In: Proceedings of the Language Resources and Evaluation Conference (LREC), Athens, Greece, pp. 1487–1494 (2000)
Zhang, X., Wang, T., Chen, H.: Story link detection based on event model with uneven svm. In: Li, H., Liu, T., Ma, W.-Y., Sakai, T., Wong, K.-F., Zhou, G. (eds.) AIRS 2008. LNCS, vol. 4993, pp. 436–441. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, L., Li, F. (2011). Story Link Detection Based on Event Words. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2011. Lecture Notes in Computer Science, vol 6609. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19437-5_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-19437-5_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-19436-8
Online ISBN: 978-3-642-19437-5
eBook Packages: Computer ScienceComputer Science (R0)