Big Data Pricing Method Based On Data Utility

With the rapid development of the mobile Internet and the Internet of Things,the volume of data generated in people's production and life has increased exponentially.The huge value hidden in the data has made big data a hot spot for all walks of life.The circulation and sharing of data resources is the key to the application of big data,and the premise of data circulation is to reasonably price it.Considering that the current big data pricing methods ignore the deficiencies of the data itself and user benefits,this paper studies the big data pricing method based on data utility.Firstly,establish a data utility function through a machine learning model to quantify the value of data.At the same time,pay attention to the interests of consumers and build a big data pricing model based on Stackelberg game.Finally,use the second-hand housing evaluation data as a case study for this pricing method.The main research content of this paper includes the following aspects.(1)The related theories and methods of big data pricing are reviewed.First,the factors affecting the data value are analyzed,and the big data value evaluation model is proposed.Secondly,the data utility function and the consumer utility function are defined,and the interest game between the data product provider and the consumers in the data pricing process is analyzed.Then,the advantages and disadvantages of the current big data pricing methods are analyzed and compared.On this basis,the utility-based big data pricing method is proposed.(2)A data utility function based on machine learning is established.Based on the analysis and summary of the process of knowledge discovery and value extraction of big data,a data utility measurement method based on machine learning model is proposed.Then,a regression-based machine learning model is defined.Finally,the method of data utility measurement is described.The utility of data is reflected by the accuracy of the model and the expression of the data utility function is given.(3)The big data pricing model based on Stackelberg game is constructed.Due to the uncertainty of the value of big data,this paper uses consumer utility to measure the benefits consumers get from buying data products.The utility function of consumers and the profit function of data product providers are established.Then,the optimal data pricing that satisfies both the maximization of provider profits and consumer utility is determined.It is proved that the price of the product is the global optimal solution.(4)Application research of the big data pricing method based on data utility.The random forest model is selected as the machine learning model to measure the utility of data,and the second-hand housing data collected through the real estate website is used for case study.The results show that the utility function set in this paper is significant and can reflect the value of data well.The data utility function is substituted into the data pricing model for calculation,and the equilibrium price of the game is obtained,which is the optimal pricing of the data product.