产品评论数据驱动的质量功能展开客户需求挖掘

QFD customer needs mining driven by product review data

针对现有质量功能展开(QFD)客户需求及其权重研究所含主观因素较多,从而造成QFD分析结果客观性较差的问题,提出一种产品评论数据驱动的QFD客户需求挖掘方法。首先提出了基于关注度隐含狄利克雷分布模型完成主题提取,利用Word2Vec相似度匹配形成客户需求集合。然后基于发明问题的解决理论(TRIZ)的需求映射模型,形成了规范化客户需求表达。最后引用改进比例重要度并增设两种阈值,以改进粗数的单值权重转化规则,从而得到客户需求最终权重。将规范化客户需求及其权重输入到质量屋模型,以实现数据驱动的QFD分析。通过实例验证了所提方法的可行性和有效性。

Aiming at the problem that the existing Quality Function Deployment(QFD)customer needs and their weights contained many subjective factors,which led to the poor objectivity of QFD analysis results,a mining method for QFD customer needs driven by product review data was proposed.A topic extraction based on attention latent Dirichlet allocation was proposed,and the customer needs collection was formed by Word2Vec similarity matching.The standardized customer needs expression was formed through the needs mapping model based on TRIZ.The improved proportional importance was cited and two thresholds were added to improve the single-value weight conversion rule of rough numbers,so as to obtain the final weight of customer needs.The normalized customer needs and their weights were input into the house of quality model to achieve data-driven QFD analysis.The feasibility and effectiveness of the proposed method was verified through examples.