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Case based Indonesian closed domain question answering system with real world questions

机译:基于案例的印度尼西亚封闭域问答系统,具有现实世界中的问题

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Number of people having expertise in a certain domain is less than people who need information in that domain. In this situation, an automatic question answering (QA) system is necessary. Observing available manual QA sites on internet, the real world question that people usually ask have different expected answer type (EAT) compared to a common automatic QA. Addressing a case study of a religion domain which makes it a closed domain QA, we proposed the EAT into 6 types: LAW, DEFINITION, COMPARISON, METHOD, TIME and PERSON. Different with common QA approach, we built the QA system using case based approach which consists of two main components: Question Analyzer and Case Retriever. Related with the case based reasoning (CBR) framework, these two main components act as the Retrieve and Reuse process while the Revise and Retain process is handle by Case Retainer component. The QA system was built using available Indonesian Natural Language Processing (NLP) tools and FreeCBR as the CBR library. The experiments were done to calculate the accuracy and testing the system with unknown case. By using 77 cases collected from internet with assumption that all answers are available, the experiments achieved 97% accuracy. And by using 10 test cases for the unknown case, the similarity score calculated by the system showed that the test questions have no answer in the available case base.
机译:在某个领域具有专业知识的人数少于在该领域需要信息的人数。在这种情况下,需要一个自动问答系统。通过观察互联网上可用的手动质量检查站点,人们通常会问到的现实世界问题与普通的自动质量检查相比具有不同的预期答案类型(EAT)。针对使宗教领域成为封闭领域质量保证的宗教案例研究,我们将EAT分为6种类型:法律,定义,比较,方法,时间和人。与常见的QA方法不同,我们使用基于案例的方法构建了QA系统,该方法由两个主要组件组成:问题分析器和案例检索器。与基于案例的推理(CBR)框架相关,这两个主要组件充当“检索和重用”过程,而“修订和保留”过程由“案例保留器”组件处理。使用可用的印尼自然语言处理(NLP)工具和FreeCBR作为CBR库构建了质量检查系统。进行实验以计算准确性并在未知情况下测试系统。通过使用从互联网上收集的77个案例(假设所有答案均可用),实验达到了97%的准确性。通过对未知案例使用10个测试案例,系统计算出的相似度得分表明测试问题在可用案例库中没有答案。

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