一句话：用词嵌入从软件工程语料中提取术语关联并揭示趋势的原型工具。
软件工程领域论文数量激增，专家难以持续跟进新进展，新人进入门槛也较高。本文提出并实现一个基于词嵌入的原型工具，用于从软件工程文本语料中抽取术语及其相互关系，并展示术语趋势。作者在软件工程知识手册以及 15,233 篇研究论文的标题与摘要上训练词嵌入，并创建测试用例以验证嵌入训练的有效性。代表性示例表明，该嵌入方法有助于总结术语并发现知识库中的趋势。
The Software Engineering (SE) community is prolific, making it challenging for experts to keep up with the flood of new papers and for neophytes to enter the field. Therefore, we posit that the community may benefit from a tool extracting terms and their interrelations from the SE community's text corpus and showing terms' trends. In this paper, we build a prototyping tool using the word embedding technique. We train the embeddings on the SE Body of Knowledge handbook and 15,233 research papers' titles and abstracts. We also create test cases necessary for validation of the training of the embeddings. We provide representative examples showing that the embeddings may aid in summarizing terms and uncovering trends in the knowledge base.