@inproceedings{f56b74787ecf4cb4940c0c4054087f8f,
title = "A storm-based real-time micro-blogging burst event detection system",
abstract = "Micro-blogging is becoming an important information source of breaking news event. Since micro-blogs are real-time unbounded stream with complex relationships, traditional burst event detection techniques do not work well. This paper presents the RBEDS which is a real-time burst event detection system following Storm distributed streaming processing framework. K-Means clustering approach and burst feature detection approach are performed to identify candidate burst events, respectively. Their outputs are incorporated to generate final event detection results. Such operation is implemented as a Storm Topology. The proposed system is evaluated on a large Sina micro-blogging dataset. The achieved system performance shows that the RBEDS system may detect burst events with good timeliness, effectiveness and scalability.",
keywords = "Burst event detection, Distributed stream processing, Storm",
author = "Yiding Wang and Ruifeng Xu and Bin Liu and Lin Gui and Bin Tang",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2014.; 13th International Conference on Machine Learning and Cybernetics, ICMLC 2014 ; Conference date: 13-07-2014 Through 16-07-2014",
year = "2014",
doi = "10.1007/978-3-662-45652-1_20",
language = "English",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "186--195",
editor = "Xizhao Wang and Qiang He and Chan, {Patrick P.K.} and Witold Pedrycz",
booktitle = "Machine Learning and Cybernetics - 13th International Conference, Proceedings",
address = "Germany",
}