[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.
孙鑫瑞,孟雨,王文乐. 基于知识图谱与目标检测的微博交通事件识别*[J]. 数据分析与知识发现, 2020, 4(12): 136-147.
Sun Xinrui,Meng Yu,Wang Wenle. Identifying Traffic Events from Weibo with Knowledge Graph and Target Detection. Data Analysis and Knowledge Discovery, 2020, 4(12): 136-147.
Rosi A, Mamei M, Zambonelli F, et al. Social Sensors and Pervasive Services: Approaches and Perspectives [C]//Proceedings of 2011 IEEE International Conference on Pervasive Computing and Communications Workshops. IEEE, 2011: 525-530.
[2]
Misra A, Gooze A, Watkins K , et al. Crowdsourcing and Its Application to Transportation Data Collection and Management[J]. Transportation Research Record: Journal of the Transportation Research Board, 2014,2414(1):1-8.
[3]
Wang X, Zheng X H, Zhang Q P , et al. Crowdsourcing in ITS: The State of the Work and the Networking[J]. IEEE Transactions on Intelligent Transportation Systems, 2016,17(6):1596-1605.
[4]
Wang F Y . The Emergence of Intelligent Enterprises: From CPS to CPSS[J]. IEEE Intelligent Systems, 2010,25(4):85-88.
[5]
Wang F Y . Real-Time Social Transportation with Online Social Signals[J]. IEEE Transactions on Intelligent Transportation Systems, 2014,15(3):909-914.
( Wang Feiyue . A Framework for Social Signal Processing and Analysis: From Social Sensing Networks to Computational Dialectical Analytics[J]. Chinese Science: Information Science, 2013,43(12):1598-1611.)
[7]
Wang F Y . Crowdsourcing for Field Transportation Studies and Services[J]. IEEE Transactions on Intelligent Transportation Systems, 2015,16(1):1-8.
[8]
Endarnoto S K, Pradipta S, Nugroho A S, et al. Traffic Condition Information Extraction & Visualization from Social Media Twitter for Android Mobile Application [C]//Proceedings of the 2011 International Conference on Electrical Engineering and Informatics. IEEE, 2011: 1-4.
[9]
Gutiérrez C, Figuerias P, Oliveira P, et al. Twitter Mining for Traffic Events Detection [C]//Proceedings of 2015 Science and Information Conference. IEEE, 2015: 371-378.
[10]
Wang S Z, He L F, Stenneth L, et al. Citywide Traffic Congestion Estimation with Social Media [C]//Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems. 2015.
[11]
Zheng X H, Chen W, Wang P , et al. Big Data for Social Transportation[J]. IEEE Transactions on Intelligent Transportation Systems, 2016,17(3):620-630.
doi: 10.1109/TITS.2015.2480157
[12]
Mai E, Hranac R. Twitter Interactions as a Data Source for Transportation Incidents [C]//Proceedings of Transportation Research Board 92nd Annual Meeting. 2013.
[13]
D’Andrea E, Ducange P, Lazzerini B , et al. Real-Time Detection of Traffic from Twitter Stream Analysis[J]. IEEE Transactions on Intelligent Transportation Systems, 2015,16(4):2269-2283.
[14]
Chen Y Y, Lv Y S, Wang X, et al. A Convolutional Neural Network for Traffic Information Sensing from Social Media Text [C]//Proceedings of the 20th International Conference on Intelligent Transportation Systems. IEEE, 2017.
[15]
Zhang Z H, He Q, Gao J , et al. A Deep Learning Approach for Detecting Traffic Accidents from Social Media Data[J]. Transportation Research Part C: Emerging Technologies, 2018,86:580-596.
[16]
熊佳茜 . 基于CRF的中文微博交通信息事件抽取[D]. 上海: 上海交通大学, 2014.
[16]
( Xiong Jiaxi . Civil Transportation Event Extraction from Chinese Microblogs Based on CRF[D]. Shanghai: Shanghai Jiao Tong University, 2014.)
( Qiu Peiyuan, Zhang Hengcai, Yu Li , et al. Automatic Event Labeling for Traffic Information Extraction from Microblogs[J]. Journal of Chinese Information Processing, 2017,31(2):107-116.)
( Zheng Zhihao, Wu Wenbing, Chen Xin , et al. A Traffic Sensing and Analyzing System Using Social Media Data[J]. Acta Automatica Sinica, 2018,44(4):656-666.)
[19]
Grant-Muller S M, Gal-Tzur A, Minkov E , et al. Enhancing Transport Data Collection Through Social Media Sources: Methods, Challenges and Opportunities for Textual Data[J]. IET Intelligent Transport Systems, 2015,9(4):407-417.
doi: 10.1049/iet-its.2013.0214
[20]
Redmon J, Farhadi A . YOLOv3: An Incremental Improvement[OL]. arXiv Preprint, arXiv: 1804.02767.