Pub Date : 2025-06-01Epub Date: 2025-04-14DOI: 10.1016/j.wpi.2025.102361
Gazala Parveen, Padmavati Manchikanti
Telemedicine has been practised since digital technology emerged in the mid-to-late 20th century. It evolved with technological advancements such as satellite communication in the 1960s, the internet in the 1990s and mobile health applications in the 2000s. Today, telemedicine forms a sub-set of digital health. In telemedicine, healthcare professionals provide medical services through information and communication technologies. The patenting of telemedicine tools is quite active, encompassing advancements in software applications, medical devices, and integrated systems for remote diagnosis, monitoring, and treatment. Effective protection of intellectual property for telemedicine tools relies on organised patent management and precise claim drafting. A study on the filing trends of the patents related to telemedicine tools and patent prosecution will give a better understanding of issues related to the patenting of such technologies. It highlights new developments that are expanding the scope of patent claims, particularly the increasing integration of telemedicine and software-enabled medical devices.
{"title":"Patenting telemedicine tools: A cross-country analysis of technologies related to remote patient monitoring","authors":"Gazala Parveen, Padmavati Manchikanti","doi":"10.1016/j.wpi.2025.102361","DOIUrl":"10.1016/j.wpi.2025.102361","url":null,"abstract":"<div><div>Telemedicine has been practised since digital technology emerged in the mid-to-late 20th century. It evolved with technological advancements such as satellite communication in the 1960s, the internet in the 1990s and mobile health applications in the 2000s. Today, telemedicine forms a sub-set of digital health. In telemedicine, healthcare professionals provide medical services through information and communication technologies. The patenting of telemedicine tools is quite active, encompassing advancements in software applications, medical devices, and integrated systems for remote diagnosis, monitoring, and treatment. Effective protection of intellectual property for telemedicine tools relies on organised patent management and precise claim drafting. A study on the filing trends of the patents related to telemedicine tools and patent prosecution will give a better understanding of issues related to the patenting of such technologies. It highlights new developments that are expanding the scope of patent claims, particularly the increasing integration of telemedicine and software-enabled medical devices.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"81 ","pages":"Article 102361"},"PeriodicalIF":2.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-01Epub Date: 2025-03-29DOI: 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.
{"title":"Knowledge flows in technology-intensive publicly listed company - Evidence from Chinese patent citation data","authors":"Shi Chen , Yifa Wang","doi":"10.1016/j.wpi.2025.102354","DOIUrl":"10.1016/j.wpi.2025.102354","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"81 ","pages":"Article 102354"},"PeriodicalIF":2.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"Multi-stage fine-tuning of patent domain-specific DeBERTa for advanced patent landscape on SDGs/Decarbonization","authors":"Yoshiaki Maehara , Yukimasa Shiozawa , Yoshiyuki Osabe","doi":"10.1016/j.wpi.2025.102343","DOIUrl":"10.1016/j.wpi.2025.102343","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"81 ","pages":"Article 102343"},"PeriodicalIF":2.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143471514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01Epub Date: 2025-01-10DOI: 10.1016/j.wpi.2025.102336
Susan Bates
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-November 2024. 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.
{"title":"Literature listing","authors":"Susan Bates","doi":"10.1016/j.wpi.2025.102336","DOIUrl":"10.1016/j.wpi.2025.102336","url":null,"abstract":"<div><div>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-November 2024. 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.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"80 ","pages":"Article 102336"},"PeriodicalIF":2.2,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01Epub Date: 2025-02-11DOI: 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.
{"title":"Advancing patent law with generative AI: Human-in-the-loop systems for AI-assisted drafting, prior art search, and multimodal IP protection","authors":"Luong Vu Bui","doi":"10.1016/j.wpi.2025.102341","DOIUrl":"10.1016/j.wpi.2025.102341","url":null,"abstract":"<div><div>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.</div><div>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.</div><div>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.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"80 ","pages":"Article 102341"},"PeriodicalIF":2.2,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143378445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01Epub Date: 2025-01-21DOI: 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.
{"title":"Evaluating application of large language models to biomedical patent claim generation","authors":"Feng-Chi Chen , Chia-Lin Pan , AIPlux Development Team","doi":"10.1016/j.wpi.2025.102339","DOIUrl":"10.1016/j.wpi.2025.102339","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"80 ","pages":"Article 102339"},"PeriodicalIF":2.2,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01Epub Date: 2025-01-17DOI: 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.
{"title":"Knowledge production in technological innovation system: A comprehensive evaluation using a multi-criteria framework based on patent data—a case study on hydrogen storage","authors":"Marina Flamand , Vincent Frigant , Stéphane Miollan","doi":"10.1016/j.wpi.2025.102337","DOIUrl":"10.1016/j.wpi.2025.102337","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"80 ","pages":"Article 102337"},"PeriodicalIF":2.2,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01Epub Date: 2025-01-16DOI: 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.
{"title":"Anti-acne cosmetics and cosmeceutical patentometric profile","authors":"Natália Maria Borges Ladeira , Zípora Morgana Quinteiro dos Santos , Ronise Suzuki , Alan de Souza , Marcelo Gomes Speziali","doi":"10.1016/j.wpi.2025.102338","DOIUrl":"10.1016/j.wpi.2025.102338","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"80 ","pages":"Article 102338"},"PeriodicalIF":2.2,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01Epub Date: 2024-12-25DOI: 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.
{"title":"Patent litigation mining using a large language model—Taking unmanned aerial vehicle development as the case domain","authors":"Amy J.C. Trappey , Shao-Chien Chou , Gi-Kuen J. Li","doi":"10.1016/j.wpi.2024.102332","DOIUrl":"10.1016/j.wpi.2024.102332","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"80 ","pages":"Article 102332"},"PeriodicalIF":2.2,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143512136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-01Epub Date: 2024-12-24DOI: 10.1016/j.wpi.2024.102333
Katsuyuki Kaneko , Yuya Kajikawa
Technological diversification of firms is an essential research topic as it has significant effects on their performance. However, we still lack consistent results whether the diversification has positive effects. We focus on the relevance of its measures as one of the causes of the inconsistency. This study aims to develop a technological diversification measure by including relativity of firms' technological portfolio, because major conventional methods, e.g., Herfindahl–Hirschmann Index and entropy, consider only one firm's absolute portfolio. We analyzed each firm's relative position from a common core of the industrial technologies for four global major firms in Fast Moving Consumer Goods sector. The product set of International Patent Classification (IPC) among them was defined as the core of industrial technology. We quantified firms' chronical shifts from there, and compared them with those by conventional methods. The proposed measure clarified the firms' relative positions in a manner that conventional ones cannot identify. The firms' qualitative information supported the validity of the observations. Our approach can take more IPC data into account, less affected by the largest number of IPC, which are among its advantages; it further allows for analysis from new aspects that complement the conventional “absolute technological portfolio” measures.
{"title":"Relative technological diversification measure using patent data: Analysis of firms’ strategies in the Fast Moving Consumer Goods (FMCG) sector","authors":"Katsuyuki Kaneko , Yuya Kajikawa","doi":"10.1016/j.wpi.2024.102333","DOIUrl":"10.1016/j.wpi.2024.102333","url":null,"abstract":"<div><div>Technological diversification of firms is an essential research topic as it has significant effects on their performance. However, we still lack consistent results whether the diversification has positive effects. We focus on the relevance of its measures as one of the causes of the inconsistency. This study aims to develop a technological diversification measure by including relativity of firms' technological portfolio, because major conventional methods, e.g., Herfindahl–Hirschmann Index and entropy, consider only one firm's absolute portfolio. We analyzed each firm's relative position from a common core of the industrial technologies for four global major firms in Fast Moving Consumer Goods sector. The product set of International Patent Classification (IPC) among them was defined as the core of industrial technology. We quantified firms' chronical shifts from there, and compared them with those by conventional methods. The proposed measure clarified the firms' relative positions in a manner that conventional ones cannot identify. The firms' qualitative information supported the validity of the observations. Our approach can take more IPC data into account, less affected by the largest number of IPC, which are among its advantages; it further allows for analysis from new aspects that complement the conventional “absolute technological portfolio” measures.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"80 ","pages":"Article 102333"},"PeriodicalIF":2.2,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143180293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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