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Recent studies show structured atomic event information is beneficial to represent the discourse semantic. However, extracting useful structured representation of events from open domain is a challenging problem. On one hand, previous event extraction methods on special domain, cannot be directly used for open domain because of domain limitation and predefined event pattern. On the other hand, atomic...
Using as few sensor nodes as possible for detecting composite event effectively in large area is a difficult problem, because the composite event contains multiple atomic events which needs many different types of heterogeneous nodes for cooperative monitoring, and the coverage quality would be worse if there are not enough sensor nodes. Most of the traditional methods are focusing on atomic event...
Conventional models relying on similarity utilizing low-level surface statistical, syntactic and lexical semantic features are suboptimal in contradiction recognition, especially for the large-scale data, such as the sensor and traffic data. To tackle this problem, this work treats the text and hypothesis pair as event graph and proposes a novel model based on event graph to recognize contradiction...
The event evolution mining for news corpus is beneficial for people who are less interested in the set of documents related by a topic rather than the underlying stories. Most of state-of-the-art approaches which derived from the TDT field considered events at the document level, which made different granularity for each event in evolution graph. In this paper, we consider events from a unified perspective...
This paper proposed an approach toward children surveillance using complex event processing (CEP) with sensor-based signals. Through receiving event streaming extracted from sensor signals, the system could trigger some complex events for further decision based on real-time CEP engine with event processing language (EPL). In wireless sensor network (WSN), different categories of sensing data could...
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