2016 49th Hawaii International Conference on System Sciences (HICSS) (2016)
Koloa, HI, USA
Jan. 5, 2016 to Jan. 8, 2016
Online News has become one of the most popular channels for consuming and understanding the real-world events. However, it is increasingly difficult for users to hold the full picture of massive events in a comprehensive perspective. In addition, how to motivate human to perceive the important rare events, which may trigger the subsequent emergency events, remains to be a challenge. To address these issues, we present EventPanorama, a framework to detect and visualize events. Firstly, we introduce a hybrid event detection method which combines topic modeling and Chance Discovery, and detects events more effectively by coupling multiple term-relations. Secondly, we propose a heterogeneous event-graph layout algorithm which takes the significance of events into consideration by leveraging latent co-occurrence relations to represent important rare events and thus enhance human cognition. An experiment demonstrates the superiority of EventPanorama by comparing with several benchmarks.
C. Zhang et al., "EventPanorama: A Framework for Event Detection and Visualization from Online News," 2016 49th Hawaii International Conference on System Sciences (HICSS), Koloa, HI, USA, 2016, pp. 3739-3748.