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Curious cat conversational crowd based and context aware knowledge acquisition chat bot

机译:基于好奇猫对话人群和上下文感知知识获取聊天机器人

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Acquisition of high quality structured knowledge that is immediately useful for reasoning algorithms has been a longstanding goal of the Artificial Intelligence research community. With the recent advances in crowdsourcing, the sheer number of internet users and the commercial availability of supporting platforms have come a new set of tools to tackle this problem. Although numerous systems and methods for crowdsourced knowledge acquisition had been developed and solve the problem of manpower, the issues of task preparation, financial cost, finding the right crowd, consistency, and quality of the acquired knowledge, seem to persist. In this paper we propose a new approach to address this deficit by exploiting an existing knowledge base to drive the acquisition process, address the right people, and check their answers for consistency. We conducted tests of the viability of the approach in experiments with real users, a working platform and common sense knowledge.
机译:获得对推理算法立即有用的高质量结构化知识,一直是人工智能研究界的长期目标。随着众包的最新进展,庞大的互联网用户数量和支持平台的商业可用性已经成为解决这一问题的新工具。尽管已经开发了许多用于众包知识获取的系统和方法并解决了人力资源的问题,但是任务准备,财务成本,寻找合适的人群,一致性和所获取知识的质量等问题似乎仍然存在。在本文中,我们提出了一种新方法来解决这一缺陷,方法是利用现有的知识库来推动收购流程,寻找合适的人员并检查其答案的一致性。我们在真实用户,工作平台和常识知识的实验中对这种方法的可行性进行了测试。

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