ISSN 0253-2778

CN 34-1054/N

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Research on the auction strategies and pricing of big data

  • School of Computer Science and Technology, Harbin Institute of Technology,Harbin 150001

Cite this:
https://doi.org/10.3969/j.issn.0253-2778.2018.06.007
  • Received Date: 21 September 2017
  • Accepted Date: 10 April 2018
  • Rev Recd Date: 10 April 2018
  • Publish Date: 30 June 2018
    Abstract

  • Abstract

    It is difficult to price big daga due to its diversity and sparsity, With big data auction set as background, for the problem that big data has a characteristic of replicability and that traditional auction models cannot determine how many big data items sellers should auction to get the maximum profits. A discussion is given on what auction strategies big data sellers should adopt under various circumstance to maximize their profits and on the appropriate number of winning bidders. The traditional Vickrey auction model and sequential auction model are modified, and two new auction models, which are suitable for different conditions of the auction, are proposed. Finally, the two auction models designed and relevant earnings expectations have been obtained.

    Abstract

    It is difficult to price big daga due to its diversity and sparsity, With big data auction set as background, for the problem that big data has a characteristic of replicability and that traditional auction models cannot determine how many big data items sellers should auction to get the maximum profits. A discussion is given on what auction strategies big data sellers should adopt under various circumstance to maximize their profits and on the appropriate number of winning bidders. The traditional Vickrey auction model and sequential auction model are modified, and two new auction models, which are suitable for different conditions of the auction, are proposed. Finally, the two auction models designed and relevant earnings expectations have been obtained.
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    • References(13)
  • [1]
    MASHAYEKHY L, NEJAD MM, GROSU D. A two-sided market mechanism for trading big data computing commodities[C]// IEEE International Conference on Big Data. Piscataway, NY: IEEE Press, 2015: 153-158.
    [2]
    LIN B R, KIFER D. On arbitrage-free pricing for general data queries[J]. Proceedings of the VLDB Endowment, 2014, 7(9):757-768.
    [3]
    KOUTRIS P, UPADHYAYA P, BALAZINSKAM, et al. Query-based data pricing[C]// ACM Sigmod-Sigact-Sigai Symposium on Principles of Database Systems. ACM, 2012:167-178.
    [4]
    LI C, LI D Y, MIKLAUG, et al. A theory of pricing private data[J]. ACM Transactions on Database Systems, 2014, 39(4):34.
    [5]
    刘朝阳. 大数据定价问题分析[J]. 图书情报知识, 2016，(1): 57-64.
    LIU Zhaoyang. Analysis on pricing of big data[J]. Documentation, Information & Knowledge, 2016，(1): 57-64.
    [6]
    陈筱贞. 大数据交易定价模式的选择[J]. 新经济, 2016，(18): 3-4.
    [7]
    SEN S, JOE-WONG C, HA S, et al. A survey of smart data pricing: Past proposals, current plans, and future trends[J]. ACM Computing Surveys, 2012, 46(2):1-37.
    [8]
    DING X, WANG H, ZHANGD, et al. A Fair Data Market System with Data Quality Evaluation and Repairing Recommendation[M]//Web Technologies and Applications. Cham, Switzerland: Springer International Publishing, 2015: 855-858.
    [9]
    杨琪，龚南宁. 我国大数据交易的主要问题及建议[J]. 大数据, 2015，1(2): 38-48.
    YANG Qi, GONG Nanning. Reections on big data exchange of China[J]. Big Data Research, 2015，1(2): 38-48.
    [10]
    刘洪玉, 张晓玉, 侯锡林. 基于讨价还价博弈模型的大数据交易价格研究[J]. 中国冶金教育, 2015，(6):86-91.
    [11]
    李默涵,李建中,高宏. 数据时效性判定问题的求解算法[J]. 计算机学报, 2012, 35(11): 2348-2360.
    LI Mohan, LI Jianzhong, GAO Hong. Evaluation of data currency[J]. Chinese Journal of Computers, 2012, 35(11): 2348-2360.
    [12]
    王文平. 大数据交易定价策略研究[J]. 软件, 2016, 37(10): 94-97.
    WANG Wenping. Research on big data transaction pricing strategy[J]. Computer Engineering & Software, 2016, 37(10): 94-97.
    [13]
    KRISHNA V. 拍卖理论[M]. 罗德明, 奚锡灿, 译. 北京: 中国人民大学出版社, 2010.)
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    [1]
    MASHAYEKHY L, NEJAD MM, GROSU D. A two-sided market mechanism for trading big data computing commodities[C]// IEEE International Conference on Big Data. Piscataway, NY: IEEE Press, 2015: 153-158.
    [2]
    LIN B R, KIFER D. On arbitrage-free pricing for general data queries[J]. Proceedings of the VLDB Endowment, 2014, 7(9):757-768.
    [3]
    KOUTRIS P, UPADHYAYA P, BALAZINSKAM, et al. Query-based data pricing[C]// ACM Sigmod-Sigact-Sigai Symposium on Principles of Database Systems. ACM, 2012:167-178.
    [4]
    LI C, LI D Y, MIKLAUG, et al. A theory of pricing private data[J]. ACM Transactions on Database Systems, 2014, 39(4):34.
    [5]
    刘朝阳. 大数据定价问题分析[J]. 图书情报知识, 2016，(1): 57-64.
    LIU Zhaoyang. Analysis on pricing of big data[J]. Documentation, Information & Knowledge, 2016，(1): 57-64.
    [6]
    陈筱贞. 大数据交易定价模式的选择[J]. 新经济, 2016，(18): 3-4.
    [7]
    SEN S, JOE-WONG C, HA S, et al. A survey of smart data pricing: Past proposals, current plans, and future trends[J]. ACM Computing Surveys, 2012, 46(2):1-37.
    [8]
    DING X, WANG H, ZHANGD, et al. A Fair Data Market System with Data Quality Evaluation and Repairing Recommendation[M]//Web Technologies and Applications. Cham, Switzerland: Springer International Publishing, 2015: 855-858.
    [9]
    杨琪，龚南宁. 我国大数据交易的主要问题及建议[J]. 大数据, 2015，1(2): 38-48.
    YANG Qi, GONG Nanning. Reections on big data exchange of China[J]. Big Data Research, 2015，1(2): 38-48.
    [10]
    刘洪玉, 张晓玉, 侯锡林. 基于讨价还价博弈模型的大数据交易价格研究[J]. 中国冶金教育, 2015，(6):86-91.
    [11]
    李默涵,李建中,高宏. 数据时效性判定问题的求解算法[J]. 计算机学报, 2012, 35(11): 2348-2360.
    LI Mohan, LI Jianzhong, GAO Hong. Evaluation of data currency[J]. Chinese Journal of Computers, 2012, 35(11): 2348-2360.
    [12]
    王文平. 大数据交易定价策略研究[J]. 软件, 2016, 37(10): 94-97.
    WANG Wenping. Research on big data transaction pricing strategy[J]. Computer Engineering & Software, 2016, 37(10): 94-97.
    [13]
    KRISHNA V. 拍卖理论[M]. 罗德明, 奚锡灿, 译. 北京: 中国人民大学出版社, 2010.)
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