论文标题
结构推理的需求工程中的自然语言 - 一项综合审查
Natural Language in Requirements Engineering for Structure Inference -- An Integrative Review
论文作者
论文摘要
对于机器来说，从文本中自动提取结构可能很难。但是，这些信息的启发可以为各种应用提供许多好处和机会。还已经确定了需求工程领域的福利。为了评估已完成的工作和目前可用的工作，本文的论文提供了有关自然语言处理（NLP）工程工具的综合审查。进行了这项评估是为了为将来的工作提供基础，并从统计数据中推断出见解。为了进行审查，描述了需求工程和NLP的历史以及对136多个NLP工具的评估。为了评估这些工具，定义了一组标准。结果是，目前尚无开源方法可以直接/初级提取信息结构，甚至封闭的源解决方案显示出限制，例如监督或输入限制，这消除了全自动和通用应用的可能性。结果，作者推断出当前的方法不适用，需要不同的方法。一种可以实现算法，知识库和文本语料库的个人管理的方法。
The automatic extraction of structure from text can be difficult for machines. Yet, the elicitation of this information can provide many benefits and opportunities for various applications. Benefits have also been identified for the area of Requirements Engineering. To evaluate what work has been done and is currently available, the paper at hand provides an integrative review regarding Natural Language Processing (NLP) tools for Requirements Engineering. This assessment was conducted to provide a foundation for future work as well as deduce insights from the stats quo. To conduct the review, the history of Requirements Engineering and NLP are described as well as an evaluation of over 136 NLP tools. To assess these tools, a set of criteria was defined. The results are that currently no open source approach exists that allows for the direct/primary extraction of information structure and even closed source solutions show limitations such as supervision or input limitations, which eliminates the possibility for fully automatic and universal application. As a results, the authors deduce that the current approaches are not applicable and a different methodology is necessary. An approach that allows for individual management of the algorithm, knowledge base, and text corpus is a possibility being pursued.
