Year: 2026
Type: conference-paper
Abstract: Patent similarity evaluation is essential for intellectual property analysis, yet existing methods struggle to capture the multifaceted structure of patent documents encompassing technical specifications, legal boundaries, and application contexts.We propose PatentMind, a framework that performs patent similarity assessment through a Multi-Aspect Reasoning Graph (MARG).PatentMind decomposes patent documents into three dimensions: technical features, application domains, and claim scopes, and computes dimension-specific similarity scores, which are then integrated via a context-aware dynamic weighting mechanism that emulates expert-level judgment.To facilitate evaluation, we introduce PatentSimBench, an expertannotated benchmark comprising 500 patent pairs.Experiments show that PatentMind achieves a Pearson correlation of r = 0.938 with expert annotations, substantially outperforming embedding-based, patent-specific, and prompt engineering baselines.Our framework offers interpretable, multi-dimensional assessment applicable to downstream tasks such as prior art search and infringement risk analysis.
Authors: Yongmin Yoo, Qiongkai Xu, Longbing Cao
Institution: Macquarie University
Language: English
Subfield: Management of Technology and Innovation
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7166812886