Title
Big Data Market Optimization Pricing Model Based on Data Quality
Abstract
In recent years, data has become a special kind of information commodity and promoted the development of information commodity economy through distribution. With the development of big data, the data market emerged and provided convenience for data transactions. However, the issues of optimal pricing and data quality allocation in the big data market have not been fully studied yet. In this paper, we proposed a big data market pricing model based on data quality. We first analyzed the dimensional indicators that affect data quality, and a linear evaluation model was established. Then, from the perspective of data science, we analyzed the impact of quality level on big data analysis (i.e., machine learning algorithms) and defined the utility function of data quality. The experimental results in real data sets have shown the applicability of the proposed quality utility function. In addition, we formulated the profit maximization problem and gave theoretical analysis. Finally, the data market can maximize profits through the proposed model illustrated with numerical examples.
Year
DOI
Venue
2019
10.1155/2019/5964068
COMPLEXITY
Field
DocType
Volume
Data set,Data quality,Commodity,Market price,Operations research,Artificial intelligence,Profit maximization,Quality level,Big data,Machine learning,Mathematics,Profit (economics)
Journal
2019
ISSN
Citations 
PageRank 
1076-2787
1
0.37
References 
Authors
0
3
Name
Order
Citations
PageRank
Jian Yang143.59
Chongchong Zhao25011.17
Chunxiao Xing317768.66