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- W2294879359 abstract "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." @default.
- W2294879359 created "2016-06-24" @default.
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- W2294879359 date "2016-01-01" @default.
- W2294879359 modified "2023-09-22" @default.
- W2294879359 title "EventPanorama: A Framework for Event Detection and Visualization from Online News" @default.
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- W2294879359 doi "https://doi.org/10.1109/hicss.2016.466" @default.
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