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Main Authors: Wang, Huiju, Gao, Yuanyuan, Wang, Zhengkui, Yue, Xiao
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2504.09065
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author Wang, Huiju
Gao, Yuanyuan
Wang, Zhengkui
Yue, Xiao
author_facet Wang, Huiju
Gao, Yuanyuan
Wang, Zhengkui
Yue, Xiao
contents In the era o fdat commodification,the pricing o fgraph data presents unique challenges that differ significantly from traditional data markets. This paper addresses the critical issue of node pricing within graph structures, an area that has been largely overlooked in existing literature. We introduce a novel pricing mechanism based on the concept of substitutability, inspired by economic principles, to better reflect the ntrinsic value of nodes in a graph. Unlike previous studies that assumed known prices for nodes or subgraphs, our approach emphasizes the structural significance of nodes by employing a dominator tree, utilizing the Lengauer-Tarjan algorithm to extract dominance relationships. This innovative framework allows us to derive a more realistic pricing strategy that accounts for the unique connectivity and roles of nodes within their respective networks. Our comparative experiments demonstrate that the proposed method significantly outperforms existing pricing strategies, yielding high-quality solutions across various datasets. This research aims to contribute to the existing literature by addressing an important gap and providing insights that may assist in the more effective valuation of graph data, potentially supporting improved decision-making in data-driven environments.
format Preprint
id arxiv_https___arxiv_org_abs_2504_09065
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Substitutability-Based Graph Node Pricing
Wang, Huiju
Gao, Yuanyuan
Wang, Zhengkui
Yue, Xiao
Databases
In the era o fdat commodification,the pricing o fgraph data presents unique challenges that differ significantly from traditional data markets. This paper addresses the critical issue of node pricing within graph structures, an area that has been largely overlooked in existing literature. We introduce a novel pricing mechanism based on the concept of substitutability, inspired by economic principles, to better reflect the ntrinsic value of nodes in a graph. Unlike previous studies that assumed known prices for nodes or subgraphs, our approach emphasizes the structural significance of nodes by employing a dominator tree, utilizing the Lengauer-Tarjan algorithm to extract dominance relationships. This innovative framework allows us to derive a more realistic pricing strategy that accounts for the unique connectivity and roles of nodes within their respective networks. Our comparative experiments demonstrate that the proposed method significantly outperforms existing pricing strategies, yielding high-quality solutions across various datasets. This research aims to contribute to the existing literature by addressing an important gap and providing insights that may assist in the more effective valuation of graph data, potentially supporting improved decision-making in data-driven environments.
title Substitutability-Based Graph Node Pricing
topic Databases
url https://arxiv.org/abs/2504.09065