%A Sun Xinrui,Meng Yu,Wang Wenle %T Identifying Traffic Events from Weibo with Knowledge Graph and Target Detection %0 Journal Article %D 2020 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2020.0596 %P 136-147 %V 4 %N 12 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_4984.shtml} %8 2020-12-25 %X

[Objective] This paper identifies traffic events from Weibo (microblog) posts with the help of knowledge graph and target detection techniques, aiming to address traffic management issues. [Methods] First, we constructed traffic knowledge graph and event evolution graph based on open data. Then, we identified traffic events from microblog texts. Third, we retrieved microblog images with target detection to further improve the recognition accuracy of three types of events. [Results] We examined our method with microblog data on Qingdao’s traffics in 2018. The precision of traffic event detection based on texts and images were 94.55% and 95.53%. [Limitations] More research is needed to reduce the manual construction of traffic knowledge graph, and improve the target detection algorithm. [Conclusions] The proposed method could help urban traffic management departments detect road incidents or traffic problems, and then facilitate their decision-makings.