计算机科学 ›› 2020, Vol. 47 ›› Issue (3): 48-53.doi: 10.11896/jsjkx.190700146
所属专题： 智能软件工程
康雁,崔国荣,李浩,杨其越,李晋源,王沛尧
KANG Yan,CUI Guo-rong,LI Hao,YANG Qi-yue,LI Jin-yuan,WANG Pei-yao
摘要： 随着软件数量的急剧增长以及种类的日益多样化,挖掘软件需求文本特征并对软件需求特征聚类,成为了软件工程领域的一大挑战。软件需求文本的聚类为软件开发过程提供了可靠的保障,同时降低了需求分析阶段的潜在风险和负面影响。然而,软件需求文本存在离散度高、噪声大和数据稀疏等特点,目前有关聚类的工作局限于单一类型的文本,鲜有考虑软件需求的功能语义。文中鉴于需求文本的特点和传统型聚类方法的局限性,提出了融合自注意力机制和多路金字塔卷积的软件需求聚类算法(SA-MPCN&SOM)。该方法通过自注意力机制捕获全局特征,然后基于多路金字塔卷积从不同窗口的通路深度挖掘需求文本特征,使得感知的文本片段逐倍增加,最终融合多路文本特征,利用SOM完成聚类。在软件需求数据上的实验表明,所提方法能较好地挖掘需求特征并对其聚类,性能上优于其他特征提取方式和聚类算法。
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