通信学报2026，Vol.47Issue(3)：75-89,15.DOI:10.11959/j.issn.1000-436x.2026045
基于椭球空间表征的数据动态定价方法
Dynamic data pricing via ellipsoidal space representation
摘要
Abstract
In data trading scenarios,differentiated pricing is often pursued by data owners across heterogeneous consum-ers to maximize revenue.However,consumer valuation models are typically unobservable,and price acceptance can only be inferred from binary transaction outcomes,indicating whether a transaction was accepted or rejected.To address this challenge,a dynamic pricing method based on an ellipsoidal representation of the valuation space was proposed.Consumers'valuation functions were learned by iteratively cutting the ellipsoid,and transaction prices were subse-quently set to more closely approximate true valuations at each round.In addition,an ellipsoid cutting strategy based on parallel splits was introduced,through which valuation weights were estimated more accurately and the convergence of parameter updates was accelerated.Theoretical analysis showed that the proposed method satisfied the no-arbitrage con-straint and ensured the effectiveness of the online update process.Experiments on real-world datasets demonstrated strong performance in pricing accuracy,convergence speed,and computational efficiency.关键词
数据交易/椭球空间表征/动态定价/椭球空间裁剪Key words
data trading/ellipsoidal space representation/dynamic pricing/ellipsoid cutting分类
信息技术与安全科学引用本文复制引用
余增文,李国浩,池臧博,杨力,姜奇,方志..基于椭球空间表征的数据动态定价方法[J].通信学报,2026,47(3):75-89,15.基金项目
国家自然科学基金资助项目(No.62572377,No.62472337) The National Natural Science Foundation of China(No.62572377,No.62472337) （No.62572377,No.62472337）
