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Towards Learning a Knowledge Base of Actions from Experiential Microblogs

机译:从经验微博学习知识基础

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While today's structured knowledge bases (e.g., Freebase) contain a sizable collection of information about entities, from celebrities and locations to concepts and common objects, there is a class of knowledge that has minimal coverage: actions. A large-scale knowledge base of actions would provide an opportunity for computing devices to aid and support people's reasoning about their own actions and outcomes, leading to improved decision-making and goal achievement. In this short paper, we describe our first efforts towards building a distributional representation of actions and their outcomes, as learned from the timelines of individuals posting experiential microblogs.
机译:虽然今天的结构化知识库(例如,FreeBase)包含有关实体的大量信息,从名人和地点到概念和常见对象,有一类具有最小覆盖率的知识:行动。大规模的行动知识基础将为计算设备提供机会,以帮助和支持人们对自己的行为和结果的推理,从而改善决策和目标成就。在这篇短文中,我们描述了我们努力建立行动和其结果的分布代表,从个人发布经验微博的时间表中学到的。

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