Abstract
On-line news event detection is detecting the first news report of a news event from various news sources in real time. Related to on-line news event detection, in this article, the author firstly introduces a news representation method for the news factors modeling based on the time, locations, characters (or organization), contents, and so on, and deducing a method related to the features of different types of news factors to calculate the weight of those news factors. Considering the insufficient of the traditional detection algorithms, then the author presents the algorithm of Micro-clusters-based on-line news event detection with Window-Adding and conducts an experiment based on news data which is collected in reality. The author achieved a satisfied experimental result verifying the validity of the proposed method.
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References
Allan, J., Papka, R., Lavrenko, V.: On-line new event detection and tracking. In: Proceedings of the SIGIR 1998: 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 37–45. ACM Press, New York (1998)
Zhang, H.-P., Liu, Q., Yu, H.-K., Cheng, X.-Q., Bai, S.: Chinese Name Entity Recognition Using Role Mode. Special Issue Word Formation and Chinese Language Processing of the International Journal of Computational Linguistics and Chinese Language Processing 8(2), 29–602 (2003)
Fu, Y., Zhou, M.-Q., Wang, X.-S., Luan, H.: On-line Event Detection from Web News Stream. ICPCA 2010 5th International Conference on Pervasive Computing and Applications, 105–110 (2010)
Sun, J.: The Topic Tracking Research with Document Title. Beijing City College, Beijing (2006)
Makkonen, J., Ahonen-Myka, H., Salmenkivi, M.: Simple Semmantics in Topic Detection and Tracking. Information Retrieval 7(3-4), 347–368 (2004)
Chen, F., Farahat, A., Brants, T.: Multiple Similarity Measures and Source-pair Information in Story Link Detection. In: Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, pp. 313–320. Association for Computational Linguistics, Boston (2004)
Papka, R.: On-line new event detection, clustering, and tracking. University of Massachusetts Amherst (1999)
Seo, Y.W., Sycara, K.: Text Clustering for Topic Detection. Tech. Report CMU-RI-TR-04-03, Robotics Institue, Carnegie Mellon University (January 2004)
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Zhang, H., Li, Gh. (2011). One Method for On-Line News Event Detection Based on the News Factors Modeling. In: Wang, Y., Li, T. (eds) Knowledge Engineering and Management. Advances in Intelligent and Soft Computing, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25661-5_55
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DOI: https://doi.org/10.1007/978-3-642-25661-5_55
Publisher Name: Springer, Berlin, Heidelberg
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