Abstract
News event detection is also called TDT (Topic Detection and Tracking), which is hot research field. Previous studies about TDT are general based on news headline. However, the headline in certain situations can not accurately reflect the actual content of the news. In this paper, our approaches focus on news event that extract from the websites. We propose an approach to generate the feature vectors that represent by the text summary of news rather than the whole news content or news headlines. This method is called Incremental clustering algorithm. Experimental results demonstrate the reliability and effectiveness of our method.
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References
Allan, J., Carbonell, J.G., Doddington, G., et al.: Topic detection and tracking pilot study final report (1998)
Wayne, C.L.: Multilingual topic detection and tracking: successful research enabled by corpora and evaluation. In: LREC (2000)
Allan, J., Papka, R., Lavrenko, V.: On-line new event detection and tracking. In: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 37–45. ACM (1998)
Yang, Y., Pierce, T., Carbonell, J.: A study of retrospective and on-line event detection. In: Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 28–36. ACM (1998)
Papka, R.: On-line New Event Detection, Clustering, and Tracking. University of Massachusetts Amherst (1999)
Kumaran, G., Allan, J.: Text classification and named entities for new event detection. In: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 297–304. ACM (2004)
Brants, T., Chen, F., Farahat, A.: A system for new event detection. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 330–337. ACM (2003)
Sayyadi, H., Hurst, M., Maykov, A.: Event detection and tracking in social streams. In: ICWSM (2009)
Zhang, K., Zi, J., Wu, L.G.: New event detection based on indexing-tree and named entity. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 215–222. ACM (2007)
Allan, J.: Introduction to topic detection and tracking. In: Allan, J. (ed.) Topic Detection and Tracking, pp. 1–16. Springer, New York (2002)
Kleinberg, J.: Temporal dynamics of on-line information streams. In: Data Stream Management: Processing High-Speed Data Streams (2006)
Makkonen, J., Ahonen-Myka, H., Salmenkivi, M.: Applying semantic classes in event detection and tracking. In: Proceedings of International Conference on Natural Language Processing (ICON 2002), pp. 175–183 (2002)
Li, Z., Wang, B., Li, M., et al.: A probabilistic model for retrospective news event detection. In: Proceedings of the 28th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 106–113. ACM (2005)
Makkonen, J.: Investigations on event evolution in TDT. In: Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: Proceedings of the HLT-NAACL 2003 Student Research Workshop, vol. 3, pp. 43–48. Association for Computational Linguistics (2003)
Allan, J. (ed.): Topic Detection and Tracking: Event-Based Information Organization. Springer Science and Business Media, New York (2002)
Makkonen, J., Ahonen-Myka, H., Salmenkivi, M.: Topic detection and tracking with spatio-temporal evidence. In: Sebastiani, F. (ed.) ECIR 2003. LNCS, vol. 2633, pp. 251–265. Springer, Heidelberg (2003)
Wayne, C.L.: Topic detection and tracking (TDT). In: On Workshop Held at the University of Maryland, vol. 27, p. 28 (1997)
Allan, J., Lavrenko, V., Jin, H.: First story detection in TDT is hard. In: Proceedings of the Ninth International Conference on Information and Knowledge Management, pp. 374–381. ACM (2000)
Kurt, H.: On-line New Event Detection and Tracking in a Multi-resource Environment. Bilkent University (2001)
Zhang, K., Zi, J., Wu, L.G.: New event detection based on indexing-tree and named entity. In: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 215–222. ACM (2007)
Xia, Z., Bu, Z.: Community detection based on a semantic network. Knowl. Based Syst. 26, 30–39 (2012)
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Yu, B., Zhang, X., Xia, Z. (2015). News Event Detection Based Web Big Data. In: Huang, DS., Jo, KH., Hussain, A. (eds) Intelligent Computing Theories and Methodologies. ICIC 2015. Lecture Notes in Computer Science(), vol 9226. Springer, Cham. https://doi.org/10.1007/978-3-319-22186-1_64
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DOI: https://doi.org/10.1007/978-3-319-22186-1_64
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