Abstract
Microblog platforms like Twitter have been the important sources for news events extraction. Existing works on event extraction on microblogs usually used keywords, entities, or selected microblog posts to represent events, which cannot give a detailed description for the extracted events, e.g., “when and where did the event happen? ”, “who were involved in the event?”, etc. In this paper, we aim at providing a fine-grained event extraction on microblogs. In particular, we focus on extracting the 5W1H features (i.e., when, where, who, what, whom, and how) for events on microblogs. We first perform a clustering step to partition the microblog posts into several event clusters. After that, we extract the 5W1H features for those clusters using different algorithms. Our approach is evaluated on two microblog datasets crawled from Sina Weibo, which is the most popular microblog platform in China. The experiment results demonstrate the effectiveness of our approach.
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References
Li, R., Lei, K., Khadiwala, R., Chang, K.C.: TEDAS: A Twitter-based event detection and analysis system. In: Proc. of ICDE, pp. 1273–1276 (2012)
Zhang, L., Zhang, Z., Jin, P.: Classification-based prediction on the retweet actions over microblog dataset. In: Wang, X.S., Cruz, I., Delis, A., Huang, G. (eds.) WISE 2012. LNCS, vol. 7651, pp. 771–776. Springer, Heidelberg (2012)
Zheng, L., Yang, K., Yu, Y., Jin, P.: Predicting Age Range of Users over Microblog Dataset. International Journal of Database Theory and Application 6(6), 85–94 (2013)
Chakrabarti, D., Punera, K.: Event summarization using tweets. In: Proc. of ICWSM (2011)
Wang, W., Zhao, D., Zou, L., Wang, D., Zheng, W.: Extracting 5W1H event semantic elements from Chinese online news. In: Chen, L., Tang, C., Yang, J., Gao, Y. (eds.) WAIM 2010. LNCS, vol. 6184, pp. 644–655. Springer, Heidelberg (2010)
Wang, W.: Chinese news event 5W1H semantic elements extraction for event ontology population. In: Proc. of WWW, pp. 197–202 (2012)
Choudhury, S., Breslin, J.: Extracting semantic entities and events from sports tweets. In: Proc. of #MSM, pp. 22–32 (2011)
Chinchor, N., Marsh, E.: Muc-7 information extraction task definition. In: MUC-7 (1998)
ACE (Automatic Content Extraction). Chinese Annotation Guidelines for Events. National Institute of Standards and Technology (2005)
Ji, H., Grishman, R.: Refining Event Extraction through Cross-Document Inference. In: Proc. of ACL, pp. 254–262 (2008)
Tan, H., Zhao, T., Zheng, J.: Identification of Chinese event and their argument roles. In: Proc. of CIT Workshops, pp. 14–19 (2008)
Lin, S., Jin, P., Zhao, X., Zhao, J., Yue, L.: Extracting Focused Time for Web Pages. In: Gao, H., Lim, L., Wang, W., Li, C., Chen, L. (eds.) WAIM 2012. LNCS, vol. 7418, pp. 266–271. Springer, Heidelberg (2012)
Lin, S., Jin, P., Zhao, X., Yue, L.: Exploiting Temporal Information in Web Search. Expert Systems with Applications 41(2), 331–341 (2014)
Zhao, X., Jin, P., Yue, L.: Automatic Temporal Expression Normalization with Reference Time Dynamic-Choosing. In: Proc. of COLING, pp. 1498–1506 (2010)
Zhang, Q., Jin, P., Lin, S., Yue, L.: Extracting Focused Locations for Web Pages. In: Wang, L., Jiang, J., Lu, J., Hong, L., Liu, B. (eds.) WAIM 2011. LNCS, vol. 7142, pp. 76–89. Springer, Heidelberg (2012)
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Zheng, L., Jin, P., Zhao, J., Yue, L. (2014). A Fine-Grained Approach for Extracting Events on Microblogs. In: Decker, H., Lhotská, L., Link, S., Spies, M., Wagner, R.R. (eds) Database and Expert Systems Applications. DEXA 2014. Lecture Notes in Computer Science, vol 8644. Springer, Cham. https://doi.org/10.1007/978-3-319-10073-9_22
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DOI: https://doi.org/10.1007/978-3-319-10073-9_22
Publisher Name: Springer, Cham
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