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Learning to Define Terms in the Software Domain

机译:学习在软件域中定义术语

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摘要

One way to test a person's knowledge of a domain is to ask them to define domain-specific terms. Here, we investigate the task of automatically generating definitions of technical terms by reading text from the technical domain. Specifically, we learn definitions of software entities from a large corpus built from the user forum Stack Overflow. To model definitions, we train a language model and incorporate additional domain-specific information like word co-occurrence, and ontological category information. Our approach improves previous baselines by 2 BLEU points for the definition generation task. Our experiments also show the additional challenges associated with the task and the short-comings of language-model based architectures for definition generation.
机译:测试一个人对域名知识的一种方法是要求他们定义特定于域的术语。在这里,我们调查通过从技术领域读取文本自动生成技术术语定义的任务。具体来说,我们从用户论坛堆栈溢出中学习从建立的大语料库中的软件实体的定义。为了模拟定义,我们培训语言模型,并将其他特定于域的信息,如Word Co-Feationence和Ontological类信息。我们的方法通过2个BLEU积分改善了前一个基线,用于定义生成任务。我们的实验还展示了与任务相关的额外挑战以及用于定义生成的基于语言模型的架构的短暂转移。

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