@inproceedings{ge2016event,
author = {Ge, Tao and Cui, Lei and Chang, Baobao and Sui, Zhifang and Zhou, Ming},
title = {Event Detection with Burst Information Networks},
booktitle = {COLING 2016},
year = {2016},
month = {December},
abstract = {Retrospective event detection is an important task for discovering previously unidentified events in a text stream. In this paper, we propose two fast centroid-aware event detection models based on a novel text stream representation – Burst Information Networks (BINets) for addressing the challenge, following the D2N2K (Data-to-Network-to-Knowledge) paradigm. The BINets are time-aware, efficient and can be easily analyzed for identifying key information (centroids). These advantages allow the BINet-based approaches to achieve the state-of-the-art performance on multiple datasets, demonstrating the efficacy of BINets for the task of event detection.},
url = {http://approjects.co.za/?big=en-us/research/publication/event-detection-burst-information-networks/},
}