论文标题
自然语言处理技术的分类工程
Classification of Natural Language Processing Techniques for Requirements Engineering
论文作者
论文摘要
从1980年代最初的努力到机器学习（ML）和深度学习（DL）技术的最新尝试，将自然语言处理（NLP）技术应用于需求工程（RE）任务的研究涵盖了40多年。但是，尽管取得了进展，但我们最近的调查表明，在RE中，仍然缺乏对常用NLP技术的系统理解和组织。我们认为，该行业面临的一个障碍是缺乏对NLP技术的共同知识及其在重新任务中的使用。在本文中，我们提出了合成和组织57种最常用的NLP技术的努力。我们通过两种方式对这些NLP技术进行了分类：首先，通过其在典型管道中的NLP任务，其次通过其语言学家分析级别进行分类。我们认为，这两种分类方式是互补的，有助于更好地理解RE中的NLP技术，而这种理解对于开发更好的NLP工具至关重要。
Research in applying natural language processing (NLP) techniques to requirements engineering (RE) tasks spans more than 40 years, from initial efforts carried out in the 1980s to more recent attempts with machine learning (ML) and deep learning (DL) techniques. However, in spite of the progress, our recent survey shows that there is still a lack of systematic understanding and organization of commonly used NLP techniques in RE. We believe one hurdle facing the industry is lack of shared knowledge of NLP techniques and their usage in RE tasks. In this paper, we present our effort to synthesize and organize 57 most frequently used NLP techniques in RE. We classify these NLP techniques in two ways: first, by their NLP tasks in typical pipelines and second, by their linguist analysis levels. We believe these two ways of classification are complementary, contributing to a better understanding of the NLP techniques in RE and such understanding is crucial to the development of better NLP tools for RE.
