World Patent Information最新文献

英文中文

Knowledge flows in technology-intensive publicly listed company - Evidence from Chinese patent citation data

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-03-29 DOI: 10.1016/j.wpi.2025.102354

Shi Chen , Yifa Wang

This empirical study utilizes patent citations from technology-intensive publicly listed companies in China between 2000 and 2019 to analyze the current state of knowledge flow within and among these companies. While capital markets are crucial for innovation, the extent to which publicly listed firms facilitate knowledge flow remains unclear. This research delineates the circulation of technological knowledge both intra- and inter-company, across similar and disparate industries, and between listed companies and non-listed innovative entities. The findings indicate a pronounced tendency among technology-intensive listed companies to cite their patents extensively. Self-citations comprise nearly 60 % of total citations, suggesting that technological knowledge primarily circulates within individual companies. Furthermore, the exchange of technological knowledge among different listed companies within the same industry is notably sparse, with only a fractional increase in the frequency of knowledge flows within the industry compared to across industry boundaries. Predominantly, the technological knowledge that technology-intensive listed companies acquire from non-listed innovative entities stems from domestic unlisted companies, with foreign entities and universities contributing to a lesser extent. When examining the spillover of technological knowledge to non-listed innovative entities, it is observed that other non-listed companies predominantly absorb such knowledge, with universities and individual innovators receiving lesser proportions. Finally, this study is significant as it provides empirical evidence on the flow of technological knowledge within and between publicly listed technology-intensive companies in China, revealing the dominance of self-citations and limited cross-company knowledge exchange. By analyzing patent citation data, this research provides valuable insights into the interactions between listed companies and non-listed innovative entities. The findings highlight the significant role of non-listed firms, universities, and foreign entities in shaping technological development. Strengthening these connections can further foster innovation and en hance knowledge diffusion across sectors.

本实证研究利用 2000 年至 2019 年间中国技术密集型上市公司的专利引用情况，分析这些公司内部和之间的知识流动现状。虽然资本市场对创新至关重要，但上市公司在多大程度上促进了知识流动仍不清楚。本研究描述了技术知识在公司内部和公司之间、同类行业和不同行业之间以及上市公司和非上市创新实体之间的流通情况。研究结果表明，技术密集型上市公司有广泛引用其专利的明显趋势。自我引用占总引用量的近 60%，这表明技术知识主要在单个公司内部流通。此外，同一行业内不同上市公司之间的技术知识交流明显稀少，与跨行业相比，行业内的知识流动频率仅有零点几的增长。技术密集型上市公司从非上市创新实体获得的技术知识主要来自国内非上市公司，外国实体和大学的贡献较小。在研究技术知识向非上市创新实体的溢出时，发现其他非上市公司主要吸收这些知识，而大学和个人创新者获得的比例较小。最后，本研究的重要意义在于为中国技术密集型上市公司内部和之间的技术知识流动提供了实证证据，揭示了自我引用占主导地位和跨公司知识交流有限的问题。通过分析专利引用数据，本研究为上市公司与非上市创新实体之间的互动提供了有价值的见解。研究结果凸显了非上市公司、大学和外国实体在影响技术发展方面的重要作用。加强这些联系可以进一步促进创新，推动跨行业的知识传播。

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引用次数: 0

Progress in patent technologies for methane catalytic combustion catalysts research

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-03-27 DOI: 10.1016/j.wpi.2025.102355

Bo Yuan , Tao Zhu , Meidan Wang , Xueli Zhang , Chen Li , Xinyue Zhang , Xudong Xu , Qian Sun

Catalytic combustion is an important approach to the effective utilization of methane, with the key being the search for efficient catalysts to maximize catalytic activity and resistance to poisoning. This work is based on the IncoPat commercial global patent database, combined with search results from the China Patent Abstracts database and the Derwent World Patents Index database, employing patent analysis methods to conduct a comprehensive analysis of the development trends in the global methane catalytic combustion catalyst materials technology field. By analyzing the trends in patent application and patent family numbers, the distribution of applicant countries/organizations, and leading applicants, this study summarizes the classification, preparation methods, and other technical key points of methane catalytic combustion catalyst materials, clarifying the latest developments in global methane catalytic combustion catalyst materials technology. This provides technical references for companies producing methane combustion catalytic materials in terms of product development and patent strategy layout, and supports the rapid development of the global methane combustion catalytic materials industry. The research findings indicate that global methane catalytic combustion catalyst technology is in a phase of rapid development, with research and applications in this field accelerating globally among countries and organizations, displaying intense technological competition and cooperation trends. Future research will focus on enhancing the activity, stability, and resistance to poisoning of catalysts, to aid in methane reduction and provide technical support for achieving global climate goals.

催化燃烧是有效利用甲烷的重要途径，关键在于寻找高效催化剂，最大限度地提高催化活性和抗中毒能力。本研究基于 IncoPat 全球商业专利数据库，结合中国专利文摘数据库和德文特世界专利索引数据库的检索结果，采用专利分析方法，对全球甲烷催化燃烧催化剂材料技术领域的发展趋势进行了全面分析。本研究通过对专利申请量、专利族数量变化趋势、申请人国别/机构分布、主要申请人等方面的分析，总结了甲烷催化燃烧催化剂材料的分类、制备方法等技术要点，阐明了全球甲烷催化燃烧催化剂材料技术的最新发展动态。这为甲烷燃烧催化材料生产企业在产品研发、专利战略布局等方面提供了技术参考，助力全球甲烷燃烧催化材料产业的快速发展。研究结果表明，全球甲烷催化燃烧催化剂技术正处于快速发展阶段，各国、各组织在该领域的研究和应用在全球范围内加速推进，呈现出激烈的技术竞争与合作趋势。未来的研究重点将放在提高催化剂的活性、稳定性和抗中毒能力上，以帮助甲烷减排，为实现全球气候目标提供技术支持。

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引用次数: 0

Literature listing

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-03-24 DOI: 10.1016/j.wpi.2025.102351

Susan Bates (Independent Researcher)

Welcome to the latest quarterly Literature Listing intended as a current awareness service for readers indicating newly published books, journal, and conference articles on IP management; Information Retrieval Techniques; Patent Landscapes; Education & Certification; and Legal & Intellectual Property Office Matters. The current Literature Listing was compiled mid-February 2025. Key resources include Scopus, Digital Commons, publishers' RSS feeds, and serendipity! This article gives a selection of interesting references to whet your appetite - the full list of references can be found in the companion datafile.

引用次数: 0

Patent litigation mining using a large language model—Taking unmanned aerial vehicle development as the case domain

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.

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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

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.

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

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.

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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

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.

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引用次数: 0

Evaluating application of large language models to biomedical patent claim generation

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.

引用次数: 0

Innovations in response to the COVID-19 pandemic: The role of non-profit and public institutions

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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