CAJ | 학술논문

针对基于在线客户评论数据进行客户细分分析的问题,设计了二阶段客户细分分析框架。在客户偏好建模阶段,设计了同义属性识别方法和属性偏好换算方法,基于产品属性树结构,构建粒度统一的客户偏好向量;在客户聚类阶段,设计了包含最优聚类数识别的聚类流程,基于模糊C均值聚类方法,对客户进行聚类。
침대기우재선객호평론수거진행객호세분분석적문제,설계료이계단객호세분분석광가。재객호편호건모계단,설계료동의속성식별방법화속성편호환산방법,기우산품속성수결구,구건립도통일적객호편호향량;재객호취류계단,설계료포함최우취류수식별적취류류정,기우모호C균치취류방법,대객호진행취류。
Traditional customer segmentation methods predominately rely on high-cost market survey,in which data is subjective.As a real expression of customers,online customer reviews（OCR）contain valuable information for customer segmentation analysis.To solve OCR-based customer segmentation problem,this research proposes a two-stage customer segmentation framework.In the user modeling stage,an synonymous attribute recognition method and an attribute utility conversion method are designed,combining with tree structure of product attributes,to build a granularity unified user preference vector;in user clustering stage,Fuzzy C-Means（FCM）-based clustering process including an optimal cluster number identification method is developed for user clustering.Empirical studies justify the effectiveness of the proposed method.