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The exponential growth of online videos, along with increasing user involvement in video-related activities, has been observed as a constant phenomenon during the last decade. User's time spent on video capturing, editing, uploading, searching, and viewing has boosted to an unprecedented level. The massive publishing and sharing of videos has given rise to(More)
We describe an efficient one-pot regio- and stereoselective method for synthesizing diverse 1-hydroxy-12H-6,12-methanodibenzo[d,g][1,3]dioxocines and 3-hydroxy-12H-6,12-methanodibenzo[d,g][1,3]dioxocines using ethylenediammonium diacetate (EDDA) or p-toluenesulfonic acid (PTSA) catalyzed reactions between various resorcinols and a number of(More)
In this paper, we introduce a new setting for graph embedding, which considers embedding communities instead of individual nodes. Community embedding is useful as a natural community representation for applications, and it provides an exciting opportunity to improve community detection. Specifically, we see the interaction between community embedding and(More)
An application sandbox model based on system call context is proposed and applied to intrusion detection. It overcomes some drawbacks of traditional special-purpose sandboxes: inconvenience for selecting sandbox with user involvement and inaccuracy of intrusion detection for different applications of the same class. The application sandbox, modeling for an(More)
As one of the most representative social media platforms, Twitter provides various real-life information on social events in real time. Despite that social event detection has been actively studied, tweet images, which appear in around 36 percent of the total tweets, have not been well utilized for this research problem. Most existing event detection(More)
Tweet streams provide a variety of real-life and real-time information on social events that dynamically change over time. Although social event detection has been actively studied, how to efficiently monitor evolving events from continuous tweet streams remains open and challenging. One common approach for event detection from text streams is to use(More)
Effective event modeling allows accurate event identification and monitoring to enable timely response to emergencies occurring in various applications. Although event identification (or detection) has been extensively studied in the last decade, the triggering relationship among initial and subsequent events has not been well studied, which limits the(More)
With the rapid growth in popularity of social websites, social event detection has become one of the hottest research topics. However, continuously monitoring social events has not been well studied. In this demo, we present a novel system called EventEye to effectively monitor evolving events and visualize their evolving paths, which are discovered from(More)