针对设计理性的自动聚类问题,提出一种基于密度峰值法的设计理性聚类方法.该方法结合设计理性的语义特点,利用单元本词汇频率/单元本频率值方法将设计理性转化为特征向量.然后基于密度峰值法求出每个特征向量的局部密度和距离两个参数,绘制决策图确定聚类中心,并将其余的数据指派到相应所属的类别中.针对密度峰值法在处理密度分布不均的数据时聚类效果差的问题,利用K最近邻方法定义动态截断距离来改进局部密度函数.以某机械设计团队的55个设计理性为例验证了所提方法的有效性.%To solve the design rationale automatic clustering problem,a design rationale clustering method by using density peaks clustering was proposed.Combined with the semantic features of design rationale,the design rationale was transformed into the feature vector with TF-IDF method.The local density and distance of each vector was obtained based on density peaks clustering.These two parameters were expressed as the decision graph,and the remaining data points were assigned to the same cluster as its nearest neighbor of higher density.Aiming at the problem that density peaks clustering could not deal with data of uneven distribution,the dynamic cut-off distance was defined to improve the local density function.55 design rationale examples from a mechanical design team were illustrated to prove the effectiveness of the proposed method.
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