【作者】 赵晨；

【导师】 刘金飞；

【作者基本信息】 浙江大学 ， 网络空间安全， 2024， 硕士

【摘要】 当今社会,数据已经成为了一种重要的资源,数据市场也随之兴起。在数据市场中,数据产品需要大量的高质量数据,来自不同来源的数据非常丰富,但它们高度分散,这给数据聚合带来了重大挑战。如何公平地量化单个数据的价值,是新兴数据市场领域的一个重要课题。源自博弈论中合作博弈的值方法是一种已被广泛应用在其他领域并收效显著的方法。数据市场中数据常以数据集的形式进行流通,其天然具有联盟结构,因此将Owen提出的解决具有层级联盟结构的合作博弈的Owen值方法应用于量化数据的价值是非常自然的。传统的Owen值计算假设数据点是稳定不变的,然而在实际应用中,数据集往往会随着新数据点的加入或旧数据点的删除而动态变化。因为从头开始重新计算Owen值的成本高得令人望而却步,所以对这种动态数据进行定价更具挑战性。针对这一问题,本文提出了动态Owen值计算的方法,旨在通过动态添加或删除数据点来提高Owen值的计算效率和有效性。本文首先介绍了合作博弈、Shapley值和Owen值的基本概念和计算方法,然后提出了基于动态数据交互的Owen值计算模型,并设计了相应的计算方法和算法。通过在实际数据集上的实证分析,验证了所提出方法的有效性和实用性。本文的研究成果对于数据市场中的数据价值评估和交易具有重要的理论和实际意义。通过动态Owen值计算方法,可以更准确地评估数据在数据市场中的价值,提高数据交易的效率和公平性。未来的研究方向可以进一步探索动态Owen值计算方法在更广泛的数据市场场景中的应用,以及如何将该方法与其他数据价值评估方法相结合,为数据市场的发展提供更多的思路和方法。更多还原

【Abstract】 In today’s society,data has become an important resource,and data markets have emerged accordingly.In data markets,data products require a large amount of high-quality data,but data from different sources is highly dispersed,which poses significant challenges to data aggrega-tion.How to fairly quantify the value of individual data is an important issue in the emerging field of data markets.The value method derived from cooperative game theory is a method that has been widely used in other fields and has achieved remarkable results.In view of the current situation that data is often circulated in the form of data sets in the data market,which naturally has an alliance structure,it is very natural to apply Owen’s value method,which solves the co-operative game with hierarchical alliance structure,to quantify the value of data.Traditional Owen value calculation assumes that data points are stable and unchanging,but in practical applications,data sets often change dynamically with the addition of new data points or the deletion of old ones.Pricing such dynamic data is more challenging due to the prohibitively ex-pensive cost of recalculation from scratch.To address this issue,this paper proposes a method for dynamic Owen value calculation,which aims to improve the efficiency and effectiveness of Owen value calculation by dynamically adding or deleting data points.This paper first introduces the basic concepts and calculation methods of cooperative games,Shapley values,and Owen values,and then proposes a dynamic data interaction-based Owen value calculation model,and designs corresponding calculation methods and algorithms.The effectiveness and practicality of the proposed method are verified through empirical analysis on actual data sets.The research results of this paper have important theoretical and practical significance for data value evaluation and transactions in data markets.Through dynamic Owen value calculation method,the value of data in data markets can be more accurately evaluated,and the efficiency and fairness of data transactions can be improved.Future research directions can further explore the application of dynamic Owen value cal-culation method in a wider range of data market scenarios,and how to combine this method with other data value evaluation methods to provide more ideas and methods for the development of data markets.更多还原