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Machine learning based review on Development and Classification of Question-Answering Systems

机译:基于机器学习的问答系统开发和分类复习

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Humans seek information continuously. In order to make information access easier, question answering (henceforth mentioned as QA) systems are developed with which user can interact in natural language and obtain relevant response. From using primitive methodologies to making the system intelligent and self-sufficient, many significant research advancements have been made in this domain since the 1960s. In this paper, we present a survey that aims to summarize the developmental trends in implementation of QA systems over the years. The paper mentions research classified under the identified important characteristics of any QA system. Consequently, an attempt is made to get a concise picture of the most current state of research in this domain. Following the review of this research, we have identified some areas having scope for future development like conversational QA systems, enhancing cognitive abilities of QA systems, etc.
机译:人类不断寻求信息。为了使信息访问更容易,开发了问答系统(此后称为QA),用户可以使用该系统以自然语言进行交互并获得相关的响应。从使用原始方法到使系统智能和自给自足,自1960年代以来,该领域已取得了许多重要的研究进展。在本文中,我们提出了一项调查,旨在总结多年来质量保证体系实施的发展趋势。本文提到了根据任何质量保证体系已确定的重要特征进行分类的研究。因此,试图对这一领域的最新研究状况进行简明扼要的描述。在对本研究进行回顾之后,我们确定了一些具有未来发展空间的领域,例如会话式QA系统,增强QA系统的认知能力等。

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