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Automation of Question-Answer Generation

机译:质疑答复一代的自动化

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摘要

In this paper, an automatic system is proposed to generate different kinds of questions and answers from the input text. Question answer generation systems have been an interesting field of research for over decades. From generating questions for educational purposes to preparing answers to questions that could be asked in a legal proceeding, the purpose of question answer generation(QAG) systems is to reduce the tedious task of going through large texts. In our system, question-answer pairs from a given input text are generated using linguistic and statistical knowledge of text. Initially, those sentences are identified from the input text on which questions can be framed and in further steps, identified sentences are ranked in an order of importance. Built specifically for assessment purpose, the system generates multiple choices, fill-ups, true-false, binary and wh type questions based on high ranked sentences in the last step. In performance evaluation of the proposed system, it is found that the system is performing well and it is close to state of art research in the standard linguistic approach.
机译:在本文中,提出了一种自动系统来从输入文本生成不同类型的问题和答案。问题答复生成系统是几十年来的一个有趣的研究领域。从为教育目的产生问题来说,为在法律程序中准备可能被要求的问题的答案,问题答复一代(QAG)系统的目的是减少经过大文本的繁琐任务。在我们的系统中,使用给定输入文本的问题答案对使用语言和文本统计知识生成。最初,这些句子是从输入文本中识别的,在哪些问题可以框架和进一步的步骤中,确定的句子按重要性排列。专为评估目的而建立,系统在最后一步中基于高排名句子生成多种选择,填充,真假,二进制和WH键入问题。在拟议系统的性能评估中,发现该系统表现良好,它与标准语言方式接近艺术研究。

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