Research On User Experience Needs Recognition And Mining Based On Product Online Reviews

Nowadays,user-centered design has become the mainstream.In order to solve such problems as lack of means for need acquisition,ignoring user experience process,overlooking users' expectations,and ineffective mapping between requirements and product design.This article proposed a method of obtaining user experience needs based on product online review data.With the help of users' real experience data to mine their potential needs,effective product design improvement programs are formed,and data efficiency is brought into play to promote product open innovation.First,the concept of experience need is proposed for the interaction process between users and products and their use of perceived feedback.Based on the big data of product life cycle,the analysis framework of behavior,scenarios and products is formed,and the main characteristics and coupling relationship of the three are deconstructed.Then,the analysis process of user experience needs is put forward.Based on the state data in the process of experience,the user experience needs are identified and extracted by ontology semantics and emotional analysis.After standardizing,it can guide the design of human-computer interaction or improve the design of product parameters.Next,taking the shared bicycle generated in the process of domestic shared economic development as an example,this paper identifies and excavates the user experience needs based on Internet data.Obtain user experience data from multiple channels,such as Internet of Things product status data,Internet user comment data,etc.Clean and organize multi-source heterogeneous data to make it structured,use natural language processing technology and data visualization method,complete the extraction and classification of experience needs.Integrating the characteristics of channel platform to analyze the positioning of products and services.Finally,based on the formation of user experience requirements,the optimization of product configuration is analyzed.A neural network mapping model from product configuration,environmental factors and behavior habits to user satisfaction score is constructed to realize the satisfaction prediction function of various factors combination schemes under different circumstances.On this basis,the typical scenarios and customary configuration schemes are predicted and simulated,and the key factors affecting the performance and their interaction are discussed.Then the configuration combination schemes of product performance are optimized to form a guiding role for product design and manufacturing.In this dissertation,user experience needs are put forward by integrating user and product feedback.User experience data are acquired through multiple channels,data utility is brought into play,automatic acquisition of experience needs is completed,potential needs in the process of experience are excavated,and traditional needs are supplemented and perfected from a new perspective.The experience requirement is effectively mapped to the function configuration of the product,and the user's satisfaction with the performance is taken as the optimization objective to form the optimal combination scheme of various structure configurations which can be referred to in the actual product design.In theory,it is a supplement to the traditional demand theory.In practice,it implements the experience requirement in product configuration optimization.It provides a reference for enterprises to deeply abstract user usage scenarios and behavior habits,and plays a guiding role in product design and manufacturing,has broad application prospects.