Research On Data-driven Product Innovation Methods Using K-Means Clustering

Aiming at the research of product design and solution under the background of big data,taking the children's companion robot product as the design carrier of theoretical research,this paper puts forward a data-driven design problem solution approach based on K-means clustering,and constructs a data-driven design problem solution mode,model,strategy and method based on K-means clustering,which is an exploration of theoretical research and design practice of industrial design Cable.Using k-means clustering data-driven design practice activities,explore the underlying logic of design activities,research to adapt to the era of big data to solve design problems.The data generated by the product is the basis of all data-driven,and relevant phenomena and problems are demonstrated by experiments and the design practice of children's accompanying robot: relevant problems or phenomena are explained or demonstrated through the design practice of children's accompanying robot,relevant methods are obtained,and the operability of the design method is demonstrated through the design practice cases of children's accompanying robot.Through the research and exploration of K-means clustering data-driven product innovation method,the abstract model to solve the design problem is obtained,which provides different ways of product innovation design under the big data environment.It is an exploratory design practice for the design theory innovation.