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A query-based cross-language diagnosis tool for distributed decision making support

机译:基于查询的跨语言诊断工具,可为分布式决策提供支持

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摘要

A query translation-based Korean-English cross-language diagnosis (Q.-KE-CLD) tool for assisting Korean users diagnosing print defects was developed and then evaluated as a case study of distributed decision making support for nonnative English users. The first step in developing the Q-KE-CLD tool involved collecting and analyzing print defect descriptions in Korean and English. A fuzzy Bayesian model was obtained from the descriptions and the Q-KE-CLD tool was developed. The tool was then experimentally evaluated in four different universities in South Korea. Results showed that Korean subjects generated Korean queries faster (p = 0.008) when entering Korean queries. In addition, the subjects rated Korean queries as being easier to generate (p - 0.004). Untrained subjects reported that use of the Korean language made it easier to generate queries and identify print defects. The overall results suggested that query translation-based cross-language diagnosis is a feasible approach for localizing troubleshooting websites.
机译:开发了一种基于查询翻译的韩英跨语言诊断(Q.-KE-CLD)工具,该工具可帮助韩语用户诊断打印缺陷,然后作为针对非母语英语用户的分布式决策支持的案例研究进行评估。开发Q-KE-CLD工具的第一步涉及以韩语和英语收集和分析打印缺陷描述。从描述中获得了模糊贝叶斯模型,并开发了Q-KE-CLD工具。然后,该工具在韩国的四所不同大学中进行了实验评估。结果表明,韩语主题在输入韩语查询时生成韩语查询的速度更快(p = 0.008)。此外,受试者对韩文查询的评价为更易于生成(p-0.004)。未经培训的受试者报告说,使用朝鲜语使生成查询和识别打印缺陷变得更加容易。总体结果表明,基于查询翻译的跨语言诊断是一种用于对故障排除网站进行本地化的可行方法。

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