摘要
针对用户需求获取及预测模糊性、抽象性等问题,提出基于Web评论数据和专利知识获取及预测用户需求的方法。首先,采用SAS软件基于特征提取技术获取用户显性需求;然后,通过结构方程模型(SEM)分析显性需求与马斯洛需求层次的潜在关系,并确定需求权重;最后,挖掘专利知识单元结合需求等级,挖掘用户隐性需求;依据Kano属性对用户需求分类,结合需求进化定律确定用户需求进化方向。以儿童用双轮智能平衡车为例,论证此方法的可行性。
Aiming at the problems of fuzziness and abstraction in the acquisition and prediction of user requirements,a method of delve into user requirements based on acquiring the explicit requirements from Web review data and utilizing patent knowledge to mine implicit requirements. Firstly,adopting SAS software based on feature extraction technology to obtain user explicit requirements. Then,through a structural equation modeling(SEM)analyze thepotential relationship between explicit requirements and Maslow’s hierarchy of needs,besides,determine the user requirements weight at each hierarchy of needs.Finally,utilizing patent knowledge unit and the user demand level to analyze the evolution trend of user requirement to mine implicit requirements of users;According to the Kano attribute and the demand weight,the user requirements are classified from three aspects of product function,performance and appearance,meanwhile,combining the law of demand evolution,the evolution direction of user requirements is determined. Eventually,user requirements statements is formed for designers. A case study of the two-wheeled intelligent balancing vehicle for children was provided to demonstrate the feasibility and effectiveness of this method.
作者
张凤伟
曹国忠
刘帅
朱玉宁
ZHANG Feng-wei;CAO Guo-zhong;LIU Shuai;ZHU Yu-ning(Hebei University of Technology,Tianjin 300401,China;National Engineering Research Center for Technological Innovation Method and Tool,Tianjin 300130,China)
出处
《机械设计与制造》
北大核心
2020年第8期59-63,67,共6页
Machinery Design & Manufacture
基金
国家自然科学基金项目(51475137)
河北省自然科学基金项目(NO.E2015202029)
河北省高层次人才资助项目(NO.A201500113)
河北省高校百名优秀创新人才支持计划(NO.SLRC2017030)。
关键词
Web数据
专利知识
数据挖掘
需求获取
需求预测
产品设计
Web Data
Patent Knowledge
Data Mining
Requirement Acquisition
Requirement Forecasting
Product Design
