Requirement traceability is the process of identifying the inter-dependencies
between requirements. It poses a significant challenge when conducted manually,
especially when dealing with requirements at various levels of abstraction. In
this work, we propose a novel approach to automate the task of linking
high-level business requirements with more technical system requirements. The
proposed approach begins by representing each requirement using a Bag of-Words
(BOW) model combined with the Term Frequency-Inverse Document Frequency
(TF-IDF) scoring function. Then, we suggested an enhanced cosine similarity
that uses recent advances in word embedding representation to correct
traditional cosine similarity function limitations. To evaluate the
effectiveness of our approach, we conducted experiments on three well-known
datasets: COEST, WARC(NFR), and WARC(FRS). The results demonstrate that our
approach significantly improves efficiency compared to existing methods. We
achieved better results with an increase of approximately 18.4% in one of the
datasets, as measured by the F2 score.

我们提出了一种新的方法来自动化将高级业务需求与更高级的技术系统需求关联起来，该方法使用词袋模型和 TF-IDF 得分函数表示每个需求，并使用最近的词嵌入表达方式改进余弦相似度函数以提高效率。实验证明，与现有方法相比，我们的方法在某个数据集中的 F2 分数增加了约 18.4%。