World Patent Information最新文献_第3页

A patent landscape of green transition in the Indian automobile industry 印度汽车工业绿色转型的专利景观

IF 1.9 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-11-12 DOI: 10.1016/j.wpi.2025.102409

Tsewang Stanzin, Ruchi Sharma

The Indian automobile industry is experiencing a rapid technological transition, shaped by growing pressures for environmental sustainability. While scholarship has extensively examined the role of FDI in transferring clean technologies to developing economies, less attention has been paid to the evolving domestic innovation landscape and the contributions of new entrants. Addressing this gap, the present study employs patent-based analysis to map the trajectory of green and dirty technologies in India's automobile industry. Using international patent classification codes, co-occurrence network analysis, and revealed technological advantage indices, we track resident and non-resident patent filings, examine the portfolios of incumbents and startups, and explore technological linkages between clean, dirty, and grey innovations. Our results reveal a sustained increase in clean patenting activity, especially in electric vehicle technologies. However, internal combustion engine-related innovations continue to dominate due to path dependency and regulatory-driven grey innovation. Startups demonstrate high specialization in clean technologies, whereas incumbent firms retain diversified portfolios. By uncovering the heterogeneous roles of incumbents and startups and highlighting the coexistence of clean, dirty, and grey innovations, this study contributes novel insights into the green transition of a critical industrial sector in a developing economy. The findings underscore the need for targeted R&D incentives, regulatory support, and startup-oriented policies to accelerate India's transition toward sustainable mobility.

印度汽车工业正在经历一场快速的技术转型，这是由日益增长的环境可持续性压力造成的。虽然学术界广泛研究了外国直接投资在向发展中经济体转让清洁技术方面的作用，但很少注意到不断变化的国内创新情况和新进入者的贡献。为了解决这一差距，本研究采用基于专利的分析来绘制印度汽车工业中绿色和肮脏技术的发展轨迹。利用国际专利分类代码、共现网络分析和揭示的技术优势指数，我们跟踪了居民和非居民专利申请，考察了现有企业和初创企业的组合，并探讨了清洁创新、肮脏创新和灰色创新之间的技术联系。我们的研究结果显示，清洁专利活动持续增加，特别是在电动汽车技术方面。然而，由于路径依赖和监管驱动的灰色创新，内燃机相关创新继续占据主导地位。初创公司在清洁技术方面表现出高度专业化，而老牌公司则保持了多元化的投资组合。通过揭示现有企业和初创企业的异质角色，并强调清洁、肮脏和灰色创新的共存，本研究为发展中经济体中关键工业部门的绿色转型提供了新的见解。研究结果强调，需要有针对性的研发激励措施、监管支持和面向初创企业的政策，以加速印度向可持续交通的过渡。

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引用次数: 0

The role of patent intelligence in demonstrating New Active Substance status 专利情报在新原料药地位论证中的作用

IF 1.9 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-11-09 DOI: 10.1016/j.wpi.2025.102408

Paula Juckes , Catherine Pringalle

All medicines must be approved by regulatory bodies in the countries where they are to be put on the market. In Europe, this approval is called “marketing authorisation” (MA). To obtain MA, pharmaceutical companies (along with other developers of medicines such as academic institutions, or individual researchers) must submit a comprehensive marketing authorisation application (MAA) and undergo a rigorous multi-step evaluation. For this paper, the word “company or companies” will be used to cover all “medicine developers” and this term also includes individuals and institutions. In Europe, the EMA issues recommendations to the European Commission regarding the potential grant of a MA, who then makes a legally binding decision. To secure these benefits, the company must request what is called “New Active Substance” or NAS designation or status, as part of its marketing authorisation application. NAS designation requires that the medicine meets certain criteria and if adopted, it prevents other parties from bringing a generic version of it to market for 10 years. Although the NAS status is a regulatory concept with defined criteria, demonstrating that an active substance has not been previously authorised in Europe often requires significant support from the Intellectual Property Department, as this is where most research on the product and its novelty has already been conducted for patentability purposes. Further, the criteria for granting NAS status have recently been made more stringent by the EMA. Obtaining market exclusivity for a product can help predict a company's value and growth thus it is important for companies to obtain this NAS status for their products. In this article we explore how different information resources and strategies were used by our company in two case examples to help verify NAS status in Europe. These case studies are based on a presentation given at the CEPIUG conference in 2023 and are not intended to be an in-depth guide.

所有药物必须得到投放市场国家监管机构的批准。在欧洲，这种批准被称为“上市许可”（MA）。为了获得MA，制药公司（以及其他药物开发商，如学术机构或个人研究人员）必须提交一份全面的上市许可申请（MAA），并经过严格的多步骤评估。在本文中，“公司或公司”一词将用于涵盖所有“药物开发人员”，该术语也包括个人和机构。在欧洲，EMA向欧盟委员会提出关于可能授予MA的建议，然后欧盟委员会做出具有法律约束力的决定。为了确保这些好处，公司必须申请所谓的“新活性物质”或NAS指定或状态，作为其上市许可申请的一部分。NAS指定要求药物符合某些标准，如果被采用，它将阻止其他方在10年内将其仿制版本推向市场。虽然NAS状态是一个具有明确标准的监管概念，但证明活性物质以前未在欧洲获得授权通常需要知识产权部门的大力支持，因为在欧洲，大多数关于产品及其新颖性的研究已经为可专利性目的进行了。此外，EMA最近对授予NAS地位的标准进行了更严格的规定。获得产品的市场独占性可以帮助预测公司的价值和增长，因此对公司来说，为其产品获得这种NAS状态非常重要。在本文中，我们将在两个案例中探讨我们公司如何使用不同的信息资源和策略来帮助验证欧洲的NAS状态。这些案例研究基于2023年CEPIUG会议上的演讲，并不打算成为深入的指南。

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引用次数: 0

Modularizing patent knowledge for enhanced technological impact 模块化专利知识以增强技术影响

IF 1.9 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-10-23 DOI: 10.1016/j.wpi.2025.102407

L. Siddharth

Modularity is a core design principle that enables technological artefacts to remain adaptable and evolvable, while creating value, maintaining technical robustness, and protecting intellectual property. Despite the perceived advantages, modularity has mostly been theoretically argued without sufficient empirical support—primarily due to the lack of large-scale datasets of structured representations of the knowledge of technological artefacts. In this study, we leverage a recently populated dataset of over 33,800 patent knowledge graphs built by recurrently extracting facts (head entity-relationship-tail entity) from patent sentences. Considering these knowledge graphs as explicit representations of patent knowledge, we investigate the influence of modularity upon the technological impact of patents, controlling for structural and semantic variables of patent knowledge graphs. We find a consistent positive influence of modularity on technological impact—quantified by short-term (5 years) and long-term (10 years) forward citation scores. Empirically substantiating the influence of modularity argued in design theories, we develop a predictive framework combining Graph Neural Networks (GNNs) and regression models to estimate citation scores from patent knowledge graphs. Using this framework, we showcase how modifications to patent knowledge—either through re-design or re-representation—can enhance the citation scores increasingly over 5- to 10-year periods—particularly for under- or un-cited patents.

模块化是一个核心设计原则，它使技术工件能够保持适应性和进化，同时创造价值，保持技术健壮性，并保护知识产权。尽管有明显的优势，但模块化在理论上的争论大多没有足够的经验支持，主要是由于缺乏技术工件知识的结构化表示的大规模数据集。在这项研究中，我们利用了一个最近填充的超过33,800个专利知识图谱的数据集，该数据集通过从专利句子中反复提取事实（头部实体-关系实体-尾部实体）而构建。考虑到这些知识图是专利知识的显式表示，我们在控制专利知识图的结构和语义变量的情况下，研究了模块化对专利技术影响的影响。通过短期（5年）和长期（10年）前向引用得分量化，我们发现模块化对技术影响具有一致的正向影响。为了实证证明设计理论中模块化的影响，我们开发了一个结合图神经网络（GNNs）和回归模型的预测框架，以估计专利知识图谱的引用分数。利用这个框架，我们展示了对专利知识的修改——无论是通过重新设计还是重新表示——如何在5到10年的时间内不断提高被引用分数，特别是对于未被引用或未被引用的专利。

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引用次数: 0

Technological and patent landscape of biosensors for leukemia detection: Evolution, maturity, and future prospects 用于白血病检测的生物传感器的技术和专利前景：演变、成熟和未来展望

IF 1.9 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-10-22 DOI: 10.1016/j.wpi.2025.102405

María C. Otálora Trujillo, Rubén Camargo-Amado, Fiderman Machuca-Martínez

The growing demand for rapid, sensitive, and accessible diagnostic tools for early leukemia detection has driven the advancement of biosensors, particularly those based on electrochemical principles. These devices stand out for their low cost, portability, and integration into point-of-care systems, making them attractive alternatives to conventional diagnostic methods. However, doubts remain about their technological maturity and long-term prospects.

This study evaluated the evolution and technological life cycle of biosensors for leukemia detection through an integrated bibliometric and patentometric analysis. A total of 1278 scientific articles indexed in Scopus and 4756 patent families retrieved from Orbit Intelligence between 2004 and 2024 were analyzed. Of these, 2332 granted and in-force patent families were considered for technological maturity and forecasting analyses. Bibliometric mapping was performed using VOSviewer, while patent classification followed International Patent Classification codes. Logistic S-curve models (Loglet Lab 4) and Yoon's parameters were applied to estimate maturity levels and future projections.

Results reveal sustained growth in publications and patents, indicating that biosensors entered an early maturity stage in 2025, with projected technological and market relevance until approximately 2050. Among detection techniques employed in electrochemical biosensors, cyclic voltammetry accounts for the largest projected number of publications and patents, while electrochemical impedance spectroscopy shows the longest technological longevity. Differential pulse voltammetry, although less represented, remains a complementary technique.

In conclusion, biosensors represent a consolidating technology with strong potential to transform leukemia diagnostics. Patentometric analysis provides strategic intelligence to guide innovation policies, strengthen intellectual property management, and support technology transfer in this developing area.

对快速、灵敏、易获得的早期白血病检测诊断工具的需求不断增长，推动了生物传感器的发展，特别是那些基于电化学原理的生物传感器。这些设备以其低成本，便携性和集成到护理点系统而脱颖而出，使其成为传统诊断方法的有吸引力的替代品。然而，人们对它们的技术成熟度和长期前景仍然心存疑虑。本研究通过综合文献计量学和专利计量学分析，评估了用于白血病检测的生物传感器的发展和技术生命周期。分析了2004 - 2024年间Scopus检索的1278篇科学论文和Orbit Intelligence检索的4756个专利族。其中，2332个已授权和有效的专利家族被考虑用于技术成熟度和预测分析。使用VOSviewer进行文献计量制图，专利分类遵循国际专利分类代码。Logistic s曲线模型（Loglet Lab 4）和Yoon的参数用于估计成熟度水平和未来预测。结果显示，出版物和专利数量持续增长，表明生物传感器在2025年进入早期成熟阶段，预计到2050年左右才具有技术和市场相关性。在电化学生物传感器中使用的检测技术中，循环伏安法预计发表和专利数量最多，而电化学阻抗谱则显示出最长的技术寿命。差分脉冲伏安法，虽然较少代表，仍然是一种补充技术。总之，生物传感器代表了一种整合技术，具有改变白血病诊断的强大潜力。专利计量分析为指导创新政策、加强知识产权管理和支持这一发展中地区的技术转让提供了战略情报。

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引用次数: 0

Industry 5.0: Life-Cycle mapping of sustainable technologies using BERTopic-Driven patent analytics 工业5.0：使用bertopic驱动的专利分析的可持续技术的生命周期映射

IF 1.9 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-10-22 DOI: 10.1016/j.wpi.2025.102406

Heng Yang, Sheng Chen

Sustainable technologies are critical to Industry 5.0—owing to the carbon-neutrality and digital-transformation transitions. To systematically identify and evaluate key sustainable technologies, this research performed an extensive investigation of 11,253 patent documents spanning the period 2011–2025. It tackled the shortcomings of previous topic-modeling approaches and the limited incorporation of life-cycle prediction in previous research. It combined the BERTopic model with the logistic growth model—enhancing topic interpretability and enabling the dynamic assessment of technological trajectories—and thus established an integrated analytical framework. The results revealed nine core technologies that drive sustainability in Industry 5.0. Technologies that have already entered the saturation stage include wireless communications (Topic 1), smart terminals and wearables (Topic 2), human–computer interaction and data intelligence (Topic 5), advanced materials and metallurgical processing (Topic 6), optical communication and modular systems (Topic 7), and acoustic sensing and smart audio (Topic 8). In addition, computer vision (Topic 0) and energy storage and wireless power transfer (Topic 4) are projected to reach the saturation stage within the next three years. Among all the technologies analyzed, additive manufacturing (Topic 3) remains at a high-growth stage, suggesting considerable potential for further development and application. This study contributes to a better understanding of the sustainable innovation landscape of Industry 5.0 and offers specific policy implications for industry stakeholders and governments.

由于碳中和和数字化转型转型，可持续技术对工业5.0至关重要。为了系统地识别和评估关键可持续技术，本研究对2011-2025年期间的11253项专利文献进行了广泛的调查。它解决了以前的主题建模方法的缺点，以及在以前的研究中有限地纳入生命周期预测。它将BERTopic模型与logistic增长模型相结合，增强了主题的可解释性，并使技术轨迹的动态评估成为可能，从而建立了一个集成的分析框架。结果揭示了推动工业5.0可持续发展的九项核心技术。已经进入饱和阶段的技术包括：无线通信（Topic 1）、智能终端与可穿戴设备（Topic 2）、人机交互与数据智能（Topic 5）、先进材料与冶金加工（Topic 6）、光通信与模块化系统（Topic 7）、声传感与智能音频（Topic 8）。此外，计算机视觉（Topic 0）和能源存储和无线电力传输（Topic 4）预计在未来三年内达到饱和阶段。在所有分析的技术中，增材制造（主题3）仍处于高增长阶段，表明进一步发展和应用的潜力很大。本研究有助于更好地理解工业5.0的可持续创新格局，并为行业利益相关者和政府提供具体的政策建议。

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引用次数: 0

Generating patent claims with semantic novelty 产生具有语义新颖性的专利权利要求

IF 1.9 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-10-15 DOI: 10.1016/j.wpi.2025.102404

Jieh-Sheng Lee

This manuscript represents an initial step to explore the potential of leveraging generative AI to drive AI-assisted inventions. From a technical standpoint, large language models are transforming industries and driving innovation, with the patent domain being no exception. From a domain perspective, the USPTO’s recent inventorship guidance highlights that AI-assisted inventions are not categorically unpatentable, opening an exciting new frontier for inventors, patent professionals, and computer scientists. The goal of this research is to generate patent claims that exhibit a higher degree of novelty. Central to this study is the investigation of whether reinforcement learning can facilitate the generation of patent claims with such novelty. In patent law, a patent is granted when it fulfills various legal requirements, such as novelty, nonobviousness, utility, written description, and subject matter eligibility. This manuscript focuses on addressing the novelty requirement by employing reinforcement learning to generate patent claim text with a higher degree of “semantic novelty.” The semantic novelty is regarded as inversely proportional to sentence similarity, which is measured by sentence embeddings. Semantic novelty serves as a computational metric to approximate the concept of novelty as understood in patent law. In pursuit of empirical investigation, this study seeks to generate dependent claims with a higher degree of novelty relative to the independent claims, and vice versa. While the experiments presented in this manuscript are preliminary and not comprehensive, they demonstrate the efficacy of reinforcement learning and the model’s capacity to generate novel ideas, underscoring the potential of this research direction for AI-assisted inventions in the future.

这份手稿代表了探索利用生成式人工智能驱动人工智能辅助发明的潜力的第一步。从技术角度来看，大型语言模型正在改变行业并推动创新，专利领域也不例外。从领域的角度来看，美国专利商标局最近的发明指导强调，人工智能辅助的发明并不是绝对不可专利的，这为发明家、专利专业人士和计算机科学家开辟了一个令人兴奋的新领域。本研究的目的是产生具有较高新颖性的专利权利要求书。本研究的核心是调查强化学习是否可以促进具有这种新颖性的专利权利要求的产生。在专利法中，当专利满足各种法律要求，如新颖性、非显而易见性、实用性、书面描述和主题资格时，专利就被授予。本文的重点是通过使用强化学习来生成具有更高程度“语义新颖性”的专利权利要求文本，从而解决新颖性要求。语义新颖性与句子相似度成反比，句子相似度是通过句子嵌入来衡量的。语义新颖性作为一种计算度量来近似专利法中新颖性的概念。为了追求实证调查，本研究试图产生相对于独立主张具有更高新颖性的依赖主张，反之亦然。虽然本文中提出的实验是初步的，并不全面，但它们证明了强化学习的有效性和模型产生新想法的能力，强调了这一研究方向在未来人工智能辅助发明方面的潜力。

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引用次数: 0

New patent text similarity methods with a comprehensive understanding of SAO semantics 全面理解SAO语义的新专利文本相似方法

IF 1.9 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-10-11 DOI: 10.1016/j.wpi.2025.102403

Nan Wang , Ziyi Wan , Hongyu Zhao , Yingtong Hu

Patent text similarity measurement is recognized as a critical component of semantic search, due diligence, infringement detection, and litigation in intellectual property management. With the continued growth in global patent filings, conventional keyword-, citation-, and classification-based approaches have been shown to inadequately capture the contextual semantics inherent in patent documents. Subject–Action–Object (SAO) structures provide a promising semantic representation; however, their effectiveness has been limited by the scarcity of specialized Semantic Text Similarity (STS) datasets and the lack of comprehensive evaluations. In this study, a novel and comprehensive framework for patent text similarity leveraging SAO semantics is proposed. Specialized patent STS datasets were constructed from USPTO examination decisions and PTAB appeal documents, comprising a 2-point scale similarity dataset and a ranking dataset for retrieval evaluation—the first openly available benchmarks of this kind. The framework integrates multiple SAO extraction techniques, novel weighting strategies including clustering-based methods, and a variety of similarity computation approaches ranging from lexical to deep learning models. Experimental evaluations show that the proposed SAO-based framework improves retrieval accuracy by 43 % over keyword-based baselines and by 26 % over standard document embedding methods. Vector-based similarity algorithms incorporating K-means clustering weights achieved a 32 % improvement over unweighted baselines. The vector-based similarity algorithm combined with K-means clustering weights improved by 32 % compared to the unweighted baseline, while the knowledge-based similarity threshold of 0.4–0.6 achieved the maximum distinction between similar and dissimilar patents. A systematic ablation analysis identified the optimal configuration as combining SAO embeddings derived from pre-trained patent vectors with clustering-based weighting, similarity thresholds, and semantic knowledge extensions. This configuration yielded superior performance in litigation support, infringement detection, and patent retrieval, reducing the average ranking position of relevant patents from 5.7 to 2.7 and achieving top-3 retrieval in all test cases.

专利文本相似度测量被认为是知识产权管理中语义搜索、尽职调查、侵权检测和诉讼的关键组成部分。随着全球专利申请的持续增长，传统的基于关键字、引文和分类的方法已被证明不能充分捕捉专利文献中固有的上下文语义。主体-动作-对象（SAO）结构提供了一种很有前途的语义表示；然而，由于缺乏专门的语义文本相似度（STS）数据集和缺乏全面的评估，它们的有效性受到限制。本文提出了一种利用SAO语义的专利文本相似度分析框架。专门的专利STS数据集是根据USPTO审查决定和PTAB上诉文件构建的，包括一个2分制的相似性数据集和一个用于检索评估的排名数据集——这是此类公开可用的基准。该框架集成了多种SAO提取技术、新的加权策略（包括基于聚类的方法）以及从词汇模型到深度学习模型的各种相似度计算方法。实验评估表明，该框架比基于关键字的基线检索精度提高了43%，比标准文档嵌入方法提高了26%。结合K-means聚类权重的基于向量的相似性算法比未加权的基线提高了32%。与未加权基线相比，基于向量的相似度算法结合K-means聚类权重提高了32%，而基于知识的相似度阈值为0.4-0.6，实现了相似和不相似专利的最大区分。系统的烧消分析确定了最优配置，即将基于预训练专利向量的SAO嵌入与基于聚类的加权、相似阈值和语义知识扩展相结合。这种配置在诉讼支持、侵权检测和专利检索方面产生了卓越的性能，将相关专利的平均排名从5.7降至2.7，并在所有测试用例中实现了前3名的检索。

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引用次数: 0

Intellectual property and SMEs … What's the state of play? 知识产权和中小企业……目前的情况如何？

IF 1.9 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-10-08 DOI: 10.1016/j.wpi.2025.102401

Christopher T. Lohrey , Kelvin W. Willoughby

This paper investigates how small and medium-sized enterprises (SMEs) can leverage intellectual property (IP) use to enhance their innovation performance. The existing literature on IP use is typically focused on large established corporations, or discrete strategy issues related to specific topics such as patent management and lacks a comprehensive overview of IP strategy challenges for SMEs. Our study addresses this gap in the literature by conducting a systematic literature review addressing the dynamics, requirements and benefits to SMEs of the strategic accumulation, maintenance and exploitation of IP rights. Our findings indicate that SMEs may improve their innovation performance, their overall business performance and their competitive positioning by treating the management of IP as a basic business function alongside orthodox management functions such as finance, marketing, operations, and R&D. This paper makes three key contributions. First, it deepens our understanding of how the use of IP affects business functions within SMEs. Second, it advances the strategy literature by highlighting IP as an impactful if not yet widely appreciated strategic domain for managers of SMEs. Third, it connects the innovation and technology management literature, in the organizational context of SMEs, with the intellectual property literature.

本文研究了中小企业如何利用知识产权来提高其创新绩效。关于知识产权使用的现有文献通常集中在大型成熟公司，或与专利管理等特定主题相关的离散战略问题上，缺乏对中小企业知识产权战略挑战的全面概述。本研究通过对中小企业战略性积累、维护和利用知识产权的动态、要求和利益进行系统的文献综述，解决了这一文献空白。研究结果表明，中小企业将知识产权管理与传统的财务、营销、运营、研发等管理职能一起作为基本的经营职能，可以提高企业的创新绩效、整体经营绩效和竞争定位。本文做出了三个关键贡献。首先，它加深了我们对知识产权的使用如何影响中小企业业务功能的理解。其次，它通过强调知识产权作为中小企业管理者的一个有影响力的战略领域（如果尚未得到广泛认可）来推进战略文献。第三，将中小企业组织背景下的创新和技术管理文献与知识产权文献联系起来。

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引用次数: 0

AI-assisted patent drafting tools: A patent landscape & future prospectives 人工智能辅助专利起草工具：专利前景与未来展望

IF 1.9 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-10-07 DOI: 10.1016/j.wpi.2025.102402

Narender Yadav , Mukesh Kumar Kumawat , Gufran Ajmal , Khalid Bashir Mir

As of early 2020, the global patent landscape for patent drafting tools has undergone significant transformation, driven by technological advancements, increased automation, and the integration of artificial intelligence. This patent landscape analysis examines global patent filings on drafting tools using Lens.org and Scifinder to identify innovation and strategic opportunities amidst the increasing complexity and volume of worldwide patent filings. It highlights key trends, innovative features, claim types, leading inventors and applicants, jurisdictional distribution, and the technological characteristics of 122 relevant patent applications spanning 56 extended patent families, thereby providing a holistic view of ongoing innovations and research activities. Furthermore, whitespace analysis reveals technological gaps and underrepresented areas including infringement analysis tools, collaboration platforms, and automated patent drawing systems pointing to promising avenues for strategic innovation and market differentiation. In addition, this study reviews 41 patent drafting tools currently available worldwide, outlining their innovative features and associated patent applications. Overall, the study offer valuable insights for researchers, innovators, patent practitioners, and stakeholders, providing foundational knowledge and clear guidance for future developments and investments in the rapidly evolving field of patent drafting technologies.

截至2020年初，在技术进步、自动化程度提高和人工智能整合的推动下，专利起草工具的全球专利格局发生了重大转变。本专利格局分析使用Lens.org和Scifinder对起草工具的全球专利申请进行了分析，以在日益复杂和日益庞大的全球专利申请中识别创新和战略机会。它突出了主要趋势、创新特征、权利要求类型、主要发明人和申请人、管辖权分布以及跨越56个扩展专利家族的122项相关专利申请的技术特征，从而提供了正在进行的创新和研究活动的整体视图。此外，空白分析揭示了技术差距和代表性不足的领域，包括侵权分析工具、协作平台和自动专利绘图系统，指出了战略创新和市场差异化的有前途的途径。此外，本研究还回顾了目前世界上可用的41种专利起草工具，概述了它们的创新特征和相关的专利申请。总体而言，该研究为研究人员、创新者、专利从业者和利益相关者提供了宝贵的见解，为快速发展的专利起草技术领域的未来发展和投资提供了基础知识和明确的指导。

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引用次数: 0

Towards a new paradigm for patent experimentation: WPI+ 迈向专利实验的新范式：WPI+

IF 1.9 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-09-29 DOI: 10.1016/j.wpi.2025.102389

Michail Salampasis , Eleni Kamateri , Vasileios Stamatis , Mihai Lupu , Allan Hanbury , Florina Piroi

We enhance the WPI patent research collection, which is publicly accessible and free of charge, to facilitate more comparable, transparent, and reproducible experiments. This is accomplished through what we call “soft standardization” advocating the adoption of consistent methods in using the test collection. We offer data statistics, predefined collection subsets, ground-truth data for additional tasks, and open-source tools for using the collection, all on a public GitHub repository. These resources not only relieve researchers from performing essential collection analysis tasks but also implicitly guide them toward sound methods for conducting experiments with the collection. Our initiative is primarily motivated by the goal of enhancing comparability and reproducibility of patent research. This is achieved through the development of a carefully designed resource that will be continuously expanded and maintained. Our work is also driven by the observation that highly integrated Information Retrieval experiment platforms for large scale evaluation are not widely adopted by researchers. We provide examples of how the WPI+ resource/collection can be used for research on multiple patent specific tasks, including prior-art search, patent classification, and summarization. Overall, our work shows that the traditional concept of a test collection—limited to just a corpus, topics, and relevance assessments—can be broadened to support more efficient and reliable scientific experimentation.

我们加强了WPI专利研究收集，该收集是公开和免费的，以促进更具可比性、透明度和可重复性的实验。这是通过我们所谓的“软标准化”来实现的，提倡在使用测试集合时采用一致的方法。我们提供数据统计，预定义的集合子集，额外任务的真实数据，以及用于使用集合的开源工具，所有这些都在公共GitHub存储库中。这些资源不仅使研究人员从执行基本的收集分析任务中解脱出来，而且还隐含地指导他们采用合理的方法进行收集实验。我们的倡议主要是为了提高专利研究的可比性和可重复性。这是通过开发一个精心设计的资源来实现的，这个资源将不断扩大和维护。我们的工作也是由于观察到用于大规模评估的高度集成的信息检索实验平台并未被研究人员广泛采用。我们提供了如何将WPI+资源/集合用于多个专利特定任务的研究的示例，包括现有技术搜索、专利分类和摘要。总的来说，我们的工作表明，传统的测试集合概念——仅限于语料库、主题和相关评估——可以被扩展，以支持更有效和可靠的科学实验。

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