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Patent litigation mining using a large language model—Taking unmanned aerial vehicle development as the case domain 基于大语言模型的专利诉讼挖掘——以无人机开发为案例领域

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-03-01 DOI: 10.1016/j.wpi.2024.102332

Amy J.C. Trappey , Shao-Chien Chou , Gi-Kuen J. Li

As unmanned aerial vehicle (UAV), also called “drone”, swiftly advances with innovative functions and applications, the surge in patent applications has profoundly reshaped the intellectual property (IP) landscape in the UAV industry, leading to a growing number of litigations. This study is structured in two phases, aiming to develop an intelligent approach to analyzing the trend and evolution of patent litigations. The first phase involves macro- and micro-patent analyses of the related technology domain. Macro patent analysis elucidates the fundamental patent information in the drone industry, while micro patent analysis leverages the technology function matrix (TFM) to identify R&D hotspots and potentials. The second phase involves litigation (judgement) mining based on large language model (LLM). Beginning with the construction of a knowledge ontology, the domain infringement landscape can be detected through TFMs. A comparative analysis of the two-phase TFMs (i.e., both TFMs of patent and infringement allocations) is then conducted to pinpoint the key legal actions and the relevant technology. To drill deeper in infringement mining, dynamic topic modeling (DTM) is applied to analyze trends and dynamics in drone controller technology over time. This study aims to strengthen IP protection by developing an intelligent litigation mining approach that adopts large language model (LLM) and uses UAV/drone litigation studies as examples to show how the approach being applied in the industry.

随着无人驾驶飞行器（UAV）以创新的功能和应用迅速发展，专利申请的激增深刻地重塑了无人机行业的知识产权格局，导致越来越多的诉讼。本研究分为两个阶段，旨在发展一种智能的方法来分析专利诉讼的趋势和演变。第一阶段涉及相关技术领域的宏观和微观专利分析。宏观专利分析阐明了无人机行业的基本专利信息，微观专利分析利用技术功能矩阵（TFM）识别研发热点和潜力。第二阶段是基于大语言模型（LLM）的诉讼（判决）挖掘。从知识本体的构建入手，通过tfm检测领域侵权格局。然后对两阶段tfm（即专利tfm和侵权分配tfm）进行比较分析，以确定关键的法律行动和相关技术。为了更深入地挖掘侵权行为，应用动态主题建模（DTM）分析无人机控制器技术随时间变化的趋势和动态。本研究旨在通过开发一种采用大语言模型（LLM）的智能诉讼挖掘方法来加强知识产权保护，并以无人机/无人机诉讼研究为例，展示该方法如何在行业中应用。

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引用次数: 0

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-02-24 DOI: 10.1016/j.wpi.2025.102342

Massimo Barbieri

引用次数: 0

Multi-stage fine-tuning of patent domain-specific DeBERTa for advanced patent landscape on SDGs/Decarbonization 可持续发展目标/脱碳先进专利景观的专利领域特定DeBERTa多阶段微调

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-02-22 DOI: 10.1016/j.wpi.2025.102343

Yoshiaki Maehara , Yukimasa Shiozawa , Yoshiyuki Osabe

This study presents a multi-stage fine-tuning approach using DeBERTa for advanced patent analysis and landscaping on SDGs and decarbonization technologies. The method incorporates FI subclass estimation with the significant improved accuracy on extracting relevant technologies from patent documents. The model outperformed previous BERT-based approaches in various tasks and was applied to analyze Japanese and PCT international patent applications. Key findings include the continued leading R&D by Japanese companies in SDGs/decarbonization area and the rapid emergence of Chinese firms. The study also introduced the "Japio-Decarbonization Patent Index" which can identify companies filing highly decarbonization-oriented patents. This research demonstrates the effectiveness of advanced NLP techniques in patent analysis, providing valuable insights for innovation promotion and technology trend prediction in sustainable development.

本研究提出了一种多阶段微调方法，利用DeBERTa对可持续发展目标和脱碳技术进行先进的专利分析和美化。该方法结合FI子类估计，显著提高了从专利文献中提取相关技术的精度。该模型在各种任务中优于以前基于bert的方法，并应用于分析日本和PCT国际专利申请。主要发现包括日本企业在可持续发展目标/脱碳领域的研发持续领先，以及中国企业的快速崛起。该研究还引入了“日本-脱碳专利指数”，该指数可以识别申请高度脱碳导向专利的公司。本研究证明了先进的自然语言处理技术在专利分析中的有效性，为可持续发展中的创新促进和技术趋势预测提供了有价值的见解。

引用次数: 0

Advancing patent law with generative AI: Human-in-the-loop systems for AI-assisted drafting, prior art search, and multimodal IP protection 用生成式人工智能推进专利法：人工智能辅助起草、现有技术搜索和多模式知识产权保护的人在环系统

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-02-11 DOI: 10.1016/j.wpi.2025.102341

Luong Vu Bui

Generative AI and Large Language Models (LLMs) are transforming patent law by automating complex tasks that traditionally demand significant legal and technical expertise. This paper examines AI-assisted systems designed to enhance patent drafting, prior art searches, and multimodal intellectual property (IP) protection. Human-in-the-Loop (HITL) frameworks play a crucial role in ensuring that AI-generated outputs remain accurate, legally compliant, and ethically sound, augmenting human expertise rather than replacing it.

We evaluate the applicability of LLMs such as GPT-4, Claude, and Gemini for patent-related tasks, highlighting their advantages and limitations. The study also explores critical challenges, including GDPR compliance, issues of interpretability, and the impact of outdated training data. Furthermore, strategies to mitigate AI-generated “hallucinations” and optimize prompt engineering for patent-specific applications are discussed. A comparative analysis of industry-leading platforms like Google Patents, PatSnap, and LexisNexis illustrates how AI tools are being integrated into patent workflows.

The paper provides both theoretical insights and practical recommendations for integrating AI into legal systems. By addressing the technical and ethical implications of AI-generated inventions, the study underscores the importance of transparency, accountability, and robust human oversight. This research aims to guide the seamless integration of AI technologies into patent law, promoting efficiency, accuracy, and compliance in an increasingly complex innovation landscape.

生成式人工智能和大型语言模型（llm）正在通过自动化传统上需要大量法律和技术专业知识的复杂任务来改变专利法。本文探讨了旨在加强专利起草、现有技术检索和多式联运知识产权（IP）保护的人工智能辅助系统。人在循环（HITL）框架在确保人工智能生成的产出保持准确、合法和合乎道德方面发挥着至关重要的作用，增强了人类的专业知识，而不是取代了它。我们评估了GPT-4、Claude和Gemini等法学硕士在专利相关任务中的适用性，突出了它们的优势和局限性。该研究还探讨了关键挑战，包括GDPR合规性、可解释性问题以及过时培训数据的影响。此外，还讨论了减轻人工智能产生的“幻觉”和优化特定专利应用的提示工程的策略。谷歌Patents、PatSnap和LexisNexis等行业领先平台的对比分析说明了人工智能工具如何被整合到专利工作流程中。本文为将人工智能纳入法律体系提供了理论见解和实践建议。通过解决人工智能产生的发明的技术和伦理影响，该研究强调了透明度、问责制和强有力的人类监督的重要性。本研究旨在指导人工智能技术与专利法的无缝整合，在日益复杂的创新环境中提高效率、准确性和合规性。

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引用次数: 0

Analysis of patentability factors and its impact on claim protection and prosecution timelines for pharmaceutical patents 可专利性因素及其对药品专利权利要求保护和起诉时间的影响分析

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-01-22 DOI: 10.1016/j.wpi.2025.102334

Jyosna Devi Ravula , Ramakrishna Nirogi , Manthan D. Janodia

The pharmaceutical industry faces unique challenges in patent prosecution due to the broad scope of innovations that patents cover. Navigating the patent prosecution process is arduous due to various factors, including its inherent complexity and the potential for patentability rejections. The study developed a new dataset containing the Orange Book listed patents based on USFDA calendar year 2020 approvals. It aimed to analyze the patent prosecution process, specifically examining the severity of office action rejections through the patent rejection severity scale and their impact on prosecution timelines. Out of 437 patents, the claim scope significantly changed for 322 (65 primary and 257 secondary) during prosecution. The results indicated that the obviousness rejections occurred more frequently for secondary patents, with a rate of 72.76 % (187/257), compared to primary patents with 33.85 % (22/65). Further analysis revealed a strong association between the severity of office action rejections and the number of office actions (p-value of 0.0036) and prosecution time (p-value of 0.0008) for secondary patents. The study also emphasized the necessity of implementing various strategies and the use of experimental data to mitigate patentability rejections and circumvent prosecution delays. This information could provide practical insights to patent practitioners dealing with rejections.

由于专利涵盖的创新范围广泛，制药行业在专利申请方面面临着独特的挑战。由于各种因素，包括其固有的复杂性和可专利性被拒绝的可能性，专利申请过程是艰巨的。该研究开发了一个新的数据集，其中包含橙皮书中列出的基于USFDA 2020日历年批准的专利。该研究旨在分析专利审查过程，特别是通过专利驳回严重程度量表检查专利局诉讼驳回的严重程度及其对审查时间表的影响。在437项专利中，322项（65项主要专利和257项次要专利）的权利要求范围在起诉期间发生了重大变化。结果表明，二级专利的明显拒绝率为72.76%(187/257)，高于一级专利的33.85%（22/65）。进一步分析显示，二级专利的驳回程度与驳回次数（p值为0.0036）和起诉时间（p值为0.0008）之间存在很强的相关性。该研究还强调了实施各种战略和使用实验数据以减轻可专利性拒绝和避免起诉延误的必要性。这些信息可以为专利从业者处理拒绝提供实用的见解。

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引用次数: 0

Evaluating application of large language models to biomedical patent claim generation 评估大型语言模型在生物医学专利权利要求生成中的应用

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-01-21 DOI: 10.1016/j.wpi.2025.102339

Feng-Chi Chen , Chia-Lin Pan , AIPlux Development Team

Automatic patent claim generation is an emerging application of large language models (LLMs). However, the performances of general-purpose LLMs in this regard remain unclear. Here we empirically evaluate the effectiveness of four different LLMs (two from the LLaMA-2 family and two from the Mistral family) in generating biomedical patent claims. This allows comparisons between LLMs with different sizes and architectures. We show that these open-source LLMs fail to produce correctly styled patent claims despite their reported strengths in natural language tasks. Nevertheless, given selected training data and adequate fine-tuning, even relatively small LLMs can yield high-quality, correctly styled patent claims. Notably, one limitation of LLMs is that they lack the creativity and insights of human drafters. For such a professional task as claim drafting, LLMs should be considered as a digital assistant that requires human oversight.

专利权利要求自动生成是大型语言模型（llm）的一种新兴应用。然而，通用法学硕士在这方面的表现仍不清楚。在这里，我们实证评估了四种不同llm（两种来自LLaMA-2家族，两种来自Mistral家族）在产生生物医学专利权利要求方面的有效性。这允许在不同规模和架构的llm之间进行比较。我们表明，尽管这些开源法学硕士在自然语言任务中具有优势，但它们无法生成正确样式的专利权利要求书。然而，给定选定的训练数据和适当的微调，即使是相对较小的法学硕士也可以产生高质量、样式正确的专利权利要求书。值得注意的是，法学硕士的一个限制是，他们缺乏人类起草人的创造力和洞察力。对于理赔起草这样的专业任务，法学硕士应该被视为需要人类监督的数字助理。

引用次数: 0

Innovations in response to the COVID-19 pandemic: The role of non-profit and public institutions 应对COVID-19大流行的创新：非营利机构和公共机构的作用

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-01-21 DOI: 10.1016/j.wpi.2025.102340

José Alberto Solis-Navarrete

The global pandemic caused by COVID-19 has devastated health, the economy, and overall well-being. However, scientific research and technological advancements have played a crucial role in reducing vulnerability to the disease, mainly through the development and distribution of vaccines. This paper explores potential innovations arising from the pandemic, focusing on patent analysis related to COVID-19, particularly from non-profit and public institutions. This research has identified over seven thousand patents granted for medical preparations, vaccine development compounds, and diagnostic, preventative, and treatment instruments, with the United States, China, and India leading in their production. Non-profit and public institutions in Brazil, France, China, and South Korea have also contributed to developing potential innovations. The study highlights the need for a comprehensive global and regional analysis of patents related to COVID-19, regardless of their type, sector of origin, or application. This research can guide academia and public policy in fostering innovation for present and future health challenges by exploring the role and potential of public and non-profit institutions in generating social innovations.

由 COVID-19 引起的全球大流行对健康、经济和整体福祉造成了严重破坏。然而，科学研究和技术进步在降低疾病易感性方面发挥了至关重要的作用，主要是通过疫苗的开发和分发。本文重点分析了与 COVID-19 相关的专利，尤其是来自非营利机构和公共机构的专利，探讨了这一流行病可能带来的创新。研究发现，美国、中国和印度在医疗制剂、疫苗开发化合物以及诊断、预防和治疗仪器方面的专利授权超过七千项，其中美国居首位。巴西、法国、中国和韩国的非营利机构和公共机构也为开发潜在创新做出了贡献。本研究强调了对 COVID-19 相关专利进行全球和地区综合分析的必要性，无论其类型、来源部门或应用情况如何。这项研究可以指导学术界和公共政策，通过探索公共和非营利机构在产生社会创新方面的作用和潜力，促进创新，以应对当前和未来的健康挑战。

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引用次数: 0

A new indicator to evaluate the quality of patent claims of additive manufacturing applicants in the US and EP 一种评价美国和欧洲增材制造申请人专利权利要求质量的新指标

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-01-20 DOI: 10.1016/j.wpi.2025.102335

Kuo-tsan Liu, Wenchuan Chang

The quality of patent application claims determines a patent's scope of protection and legal value. This study defines a new indicator based on claims structure to measure claim coverage, evaluate individual patents, and compare the strengths and weaknesses of competitors' patent portfolios in additive manufacturing technology. The new indicator's credibility is verified by comparing literature indicators.

Claim drafting is highly influenced by the official fees and legal regulations of national patent offices. Seven main additive manufacturing companies were selected to investigate their claim drafting strategies when applying for European patents while claiming priority in the United States. The indicators are shown on 2D maps of individual patents and patent portfolios. The ATT indicator is defined by independent claims representing attack strength, the DEF indicator is defined by dependent claims representing defense ability, and the TOT indicator is the sum of both. These indicators also represent the technical value of the patented invention, because more claims can be drafted for an invention with a wider range of technologies or more embodiments. 3D Systems and Stratasys make good use of domestic claim regulations to obtain higher patent values in the United States and Europe while minimizing fees.

专利申请权利要求的质量决定了专利的保护范围和法律价值。本研究定义了一个基于权利要求结构的新指标，用于衡量权利要求的覆盖范围、评估单个专利以及比较竞争对手在增材制造技术领域专利组合的优劣。权利要求的撰写受国家专利局官方收费和法律规定的影响很大。我们选取了七家主要的增材制造公司，调查它们在申请欧洲专利时的权利要求撰写策略，以及在美国申请优先权时的权利要求撰写策略。这些指标显示在单个专利和专利组合的二维地图上。ATT 指标由代表攻击强度的独立权利要求定义，DEF 指标由代表防御能力的从属权利要求定义，而 TOT 指标则是两者的总和。这些指标也代表了专利发明的技术价值，因为一项发明的技术范围更广或实施方式更多，就可以起草更多的权利要求。3D Systems 和 Stratasys 充分利用国内权利要求法规，在美国和欧洲获得了更高的专利价值，同时将费用降到最低。

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引用次数: 0

Knowledge production in technological innovation system: A comprehensive evaluation using a multi-criteria framework based on patent data—a case study on hydrogen storage 技术创新系统中的知识生产：基于专利数据的多标准框架综合评价——以储氢技术为例

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-01-17 DOI: 10.1016/j.wpi.2025.102337

Marina Flamand , Vincent Frigant , Stéphane Miollan

Knowledge production activity is central within a technological innovation system. The number of patent applications is commonly used to evaluate this activity. However, it is subject to bias and inaccurate evaluations can occur. This article proposes a multi-criteria framework based on seven complementary patent indicators, taking into account the persistence, commitment, and coherence of knowledge production activities for a more comprehensive evaluation. We demonstrate the value of our proposal through a case study on hydrogen storage, comparing patent data since 2000 about three technological solutions: physical, chemical and adsorption technologies. Our framework clearly shows that physical hydrogen storage is the most advanced in terms of knowledge production, despite not having the highest number of patent applications.

知识生产活动是技术创新系统的核心。专利申请的数量通常用于评估这一活动。然而，它会受到偏见和不准确的评估。本文提出了一个基于七个互补专利指标的多标准框架，考虑到知识生产活动的持久性、承诺性和一致性，以进行更全面的评估。我们通过一个关于储氢的案例研究来证明我们的建议的价值，比较了自2000年以来关于三种技术解决方案的专利数据：物理、化学和吸附技术。我们的框架清楚地表明，物理储氢在知识生产方面是最先进的，尽管专利申请数量并不多。

引用次数: 0

Anti-acne cosmetics and cosmeceutical patentometric profile 抗痤疮化妆品和化妆品专利计量学简介

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-01-16 DOI: 10.1016/j.wpi.2025.102338

Natália Maria Borges Ladeira , Zípora Morgana Quinteiro dos Santos , Ronise Suzuki , Alan de Souza , Marcelo Gomes Speziali

This study delves into acne vulgaris, a chronic skin condition, marked by inflammation within the pilosebaceous unit. The significant economic burden of acne treatment is reflected in a burgeoning market poised for further expansion. Through patentometric analysis, aiming to identify technological trends, the research underscores the critical role of this method in identifying strategic opportunities within the anti-acne cosmetics and cosmeceuticals domain, pointing out China, the USA, South Korea, and Japan as pivotal in creating and consuming anti-acne technologies. The patent data reveals a pronounced focus on medicine and pharmacology, especially those derived from plant and animal sources. Patent applications have declined post-2017 suggesting shifts in research and development priorities and challenges in pioneering effective products. The applicants' temporal analysis and S-curve reflect the sector's maturity and growth trajectory. Despite the significant economic and societal burden of acne vulgaris, there is a lack of comprehensive studies that integrate patentometric insights with strategic market analysis, particularly focusing on the evolving trends in anti-acne technologies. This study includes the competitiveness indicators provided for the top companies worldwide. These indicators (e.g. patenting activity, technological share, average patent quality, patent strength, etc.) showed the strategic positioning of those actors. Ultimately, the paper proposes that the insights garnered could serve as a foundation for strategic allocation of financial and innovative efforts, underlining the need for advancements in treating acne vulgaris, a condition currently lacking a definitive cure.

本研究深入寻常痤疮，慢性皮肤病，以皮脂腺单位炎症为标志。痤疮治疗的重大经济负担反映在一个蓬勃发展的市场准备进一步扩大。通过专利计量分析，旨在确定技术趋势，该研究强调了该方法在识别抗痤疮化妆品和药妆领域的战略机会方面的关键作用，并指出中国、美国、韩国和日本是创造和消费抗痤疮技术的关键。专利数据显示了对药物和药理学的明显关注，特别是那些来源于植物和动物的药物。2017年后，专利申请数量有所下降，这表明研发重点发生了变化，并在开拓有效产品方面面临挑战。申请人的时间分析和s曲线反映了该行业的成熟度和成长轨迹。尽管寻常痤疮带来了巨大的经济和社会负担，但缺乏将专利计量学见解与战略市场分析相结合的综合研究，特别是关注抗痤疮技术的发展趋势。本研究包括为全球顶级公司提供的竞争力指标。这些指标（如专利活动、技术份额、平均专利质量、专利强度等）显示了这些行为体的战略定位。最后，论文提出，所获得的见解可以作为财政和创新努力的战略分配的基础，强调需要在治疗寻常痤疮方面取得进展，目前缺乏明确的治疗方法。

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