Journal of Guangxi Normal University(Natural Science Edition) ›› 2019, Vol. 37 ›› Issue (1): 23-31.doi: 10.16088/j.issn.1001-6600.2019.01.003

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A New Method to Detect Busty Events with Different Media Data Based on Word Clustering

LIU Jinlong1,2*,GUO Yan1, YU Zhihua1, LIU Yue1,YU Xiaoming1,CHENGXueqi1   

  1. 1.Institute of Computing Technology, Chinese Academy of Sciences, Key Laboratory of Network Date Science & Technology, Beijing 100190,China;
    2.Graduate University of Chinese Academy of Sciences, Beijing 100049,China
  • Received:2018-10-14 Published:2019-01-08

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Abstract: This paper proposes a cross-media bursty events detection method based on bursty words clustering. According to the events analysis, as Microblogs has a huge number of posts, users post or retweet Microblogs in anytime, it may spend fewer time detecting busty events than other platforms. However, many microblogs are advertisements and worthless, which leads to a lower precision. On the contrary, as an official media, news is highly authentic and authoritative, and contents of news are more standard. Therefore, events detection has a higher accuracy. However, due to the small number of news, the efficiency of busty events detection is low. At present, all of the existing detection methods only mine the data of one media, which face with a dilemma between efficiency and accuracy. In this paper, the proposed model fuses the data of two medias, microblog and newssin order to meet the needs of efficiency and improve the accuracy of emergency detection.

Key words: bursty events, detection, cross-media, hierarchical clustering

CLC Number: 

  • TP391.1
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