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Evidence record 3311 · automatically gathered

A Framework for Graph-Conditioned Hierarchical Shapley Attribution in Patent Valuation

Estimating the economic contribution of a single patent inside a product that embodies tens of thousands of patents is a long-standing unsolved problem in intellectual property economics. We propose PatentXAI, a framework that treats patent valuation as a problem of explainable AI: given a characteristic function v(S) encoding the revenue achievable by patent subset S, a patent's Shapley value measures its fair share of product profit in a way that satisfies efficiency, symmetry, dummy, and addi

Record details

Published: 1 June 2026
Source: arXiv
Category: Research
Topics: Copyright & IP · Transparency · Finance, VC & PE
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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Shared topic: Transparency · Shared topic: Finance, VC & PE

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How to cite this record

ethics.ai (1 June 2026), “A Framework for Graph-Conditioned Hierarchical Shapley Attribution in Patent Valuation,” evidence record 3311, https://ethics.ai/record/3311 (originally published by arXiv).

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