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EventNet: Inferring Temporal Relations Between Commonsense Events

机译:EventNet:推断常识事件之间的时间关系

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摘要

In this paper, we describe EventNet, a toolkit for inferring temporal relations between Commonsense events. It comprises 10,000 nodes and 30,000 temporal links mined from the Openmind Commonsense Knowledge Base. It enables applications to deduce "obvious" (to people) temporal relations between commonly occurring events, for example: First, you wake up, then you can leave the house in the morning. The temporal relation might be one of cause and effect, of action/goal or prerequisite relations, or simply that they tend to follow each other in a commonly occurring "script". In addition, the algorithm has some built-in heuristics to infer when its information is not enough. It then finds semantically similar nodes to dynamically search the knowledge base. EventNet has been used in projects such as an intelligent kitchen, and in intelligent interfaces for consumer electronics devices.
机译:在本文中,我们描述EventNet,这是一种用于推断常识事件之间的时间关系的工具包。它包含10,000个节点和30,000个时间链接,这些链接是从Openmind常识知识库中提取的。它使应用程序可以推断出常见事件之间的“明显”(对人们)暂时的关系,例如:首先,您醒来,然后可以在早上离开家。时间关系可能是因果关系,是行动/目标或先决条件关系,也可能只是它们倾向于在常见的“脚本”中相互遵循。另外,该算法具有一些内置的启发式方法,可以推断出其信息是否足够。然后,它找到语义相似的节点以动态搜索知识库。 EventNet已用于诸如智能厨房之类的项目中,以及用于消费电子设备的智能接口中。

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