Pub Date : 2026-01-14DOI: 10.1016/j.wpi.2026.102426
Nathan Monnet , Loïc Maréchal
We introduce a novel approach to text classification by combining doc2vec embeddings with advanced clustering techniques to improve the analysis of specialized, high-dimensional textual data. We integrate unsupervised methods such as Louvain, K-means, and Spectral clustering with doc2vec to enhance the detection of semantic patterns across a large corpus. As a case study, we apply this methodology to cybersecurity risk analysis using the MITRE ATT&CK framework to structure and reduce the dimensionality of cyberattack tactics. Louvain clustering proved the most effective among the tested methods, achieving the best balance between cluster coherence and computational efficiency. Our approach identifies four “super tactics”, demonstrating how clustering improves thematic coherence and risk attribution. The results validate the utility of combining doc2vec with clustering, particularly Louvain, for enhancing topic modelling and text classification.
{"title":"Clustering doc2vec output for topic-dimensionality reduction: A MITRE ATT&CK calibration","authors":"Nathan Monnet , Loïc Maréchal","doi":"10.1016/j.wpi.2026.102426","DOIUrl":"10.1016/j.wpi.2026.102426","url":null,"abstract":"<div><div>We introduce a novel approach to text classification by combining doc2vec embeddings with advanced clustering techniques to improve the analysis of specialized, high-dimensional textual data. We integrate unsupervised methods such as Louvain, K-means, and Spectral clustering with doc2vec to enhance the detection of semantic patterns across a large corpus. As a case study, we apply this methodology to cybersecurity risk analysis using the MITRE ATT&CK framework to structure and reduce the dimensionality of cyberattack tactics. Louvain clustering proved the most effective among the tested methods, achieving the best balance between cluster coherence and computational efficiency. Our approach identifies four “super tactics”, demonstrating how clustering improves thematic coherence and risk attribution. The results validate the utility of combining doc2vec with clustering, particularly Louvain, for enhancing topic modelling and text classification.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"84 ","pages":"Article 102426"},"PeriodicalIF":1.9,"publicationDate":"2026-01-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145977370","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 : 2026-01-02DOI: 10.1016/j.wpi.2025.102424
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 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.
{"title":"Literature listing","authors":"Susan Bates","doi":"10.1016/j.wpi.2025.102424","DOIUrl":"10.1016/j.wpi.2025.102424","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 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.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"84 ","pages":"Article 102424"},"PeriodicalIF":1.9,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884446","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 : 2026-01-02DOI: 10.1016/j.wpi.2025.102425
Xiaoyu Zhang, Jing Shi, Lele Kang
Can open IP strategies promote innovation among competitors, thereby advancing the development of the technology field? This empirical question has remained a central topic of debate in the open innovation literature. To address this question, this study examines how open IP strategies adopted by leading firms affect technological advancement. The patent pledges by Tesla and Toyota serve as exogenous shocks, enabling an empirical analysis of the impact of open IP strategies on technological development in the Low Emission Vehicles (LEVs) industry. We utilized Difference-in-Differences (DID) models analyzing patent data from 2010 to 2019 to measure the effects on technological performance across firms. Our results indicate that open IP strategies significantly enhance technological output, including quantity, quality, and novelty, especially benefiting start-ups, and to a lesser extent, firms with rich knowledge bases. This study contributes to understanding the role of open innovation in fostering technological competition.
{"title":"The impact of the open IP strategies on technology development: Evidence from the low emission vehicles field","authors":"Xiaoyu Zhang, Jing Shi, Lele Kang","doi":"10.1016/j.wpi.2025.102425","DOIUrl":"10.1016/j.wpi.2025.102425","url":null,"abstract":"<div><div>Can open IP strategies promote innovation among competitors, thereby advancing the development of the technology field? This empirical question has remained a central topic of debate in the open innovation literature. To address this question, this study examines how open IP strategies adopted by leading firms affect technological advancement. The patent pledges by Tesla and Toyota serve as exogenous shocks, enabling an empirical analysis of the impact of open IP strategies on technological development in the Low Emission Vehicles (LEVs) industry. We utilized Difference-in-Differences (DID) models analyzing patent data from 2010 to 2019 to measure the effects on technological performance across firms. Our results indicate that open IP strategies significantly enhance technological output, including quantity, quality, and novelty, especially benefiting start-ups, and to a lesser extent, firms with rich knowledge bases. This study contributes to understanding the role of open innovation in fostering technological competition.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"84 ","pages":"Article 102425"},"PeriodicalIF":1.9,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145884445","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 : 2025-12-20DOI: 10.1016/j.wpi.2025.102423
Milad Armani Dehghani , Mehmet Sahiner , Noptanit Chotisarn
Patents are critical indicators of innovation, especially in fast-evolving domains like Financial Technology (FinTech). However, accurately predicting patent grant outcomes with modern artificial intelligence techniques has remained challenging. This study addresses that gap by applying state-of-the-art machine learning (ML), including ensemble methods and deep learning models, to a dataset of 20,008 FinTech patent applications from 2000 to 2020. We demonstrate that our ML framework can forecast grant success with high precision (up to 89 %), revealing that patent quality and strategic filing choices, such as optimal IPC classes and jurisdictions, are key determinants of grant probability. The findings highlight practical implications for innovators and intellectual property managers, such as better resource allocation and informed patent strategy decisions. Overall, this work introduces a novel, AI-driven approach to patent analytics in FinTech, offering a forward-looking tool to enhance innovation management and strategic IP planning.
{"title":"From filing to grant: Predicting patent outcomes in FinTech using a predictive analytics perspective","authors":"Milad Armani Dehghani , Mehmet Sahiner , Noptanit Chotisarn","doi":"10.1016/j.wpi.2025.102423","DOIUrl":"10.1016/j.wpi.2025.102423","url":null,"abstract":"<div><div>Patents are critical indicators of innovation, especially in fast-evolving domains like Financial Technology (FinTech). However, accurately predicting patent grant outcomes with modern artificial intelligence techniques has remained challenging. This study addresses that gap by applying state-of-the-art machine learning (ML), including ensemble methods and deep learning models, to a dataset of 20,008 FinTech patent applications from 2000 to 2020. We demonstrate that our ML framework can forecast grant success with high precision (up to 89 %), revealing that patent quality and strategic filing choices, such as optimal IPC classes and jurisdictions, are key determinants of grant probability. The findings highlight practical implications for innovators and intellectual property managers, such as better resource allocation and informed patent strategy decisions. Overall, this work introduces a novel, AI-driven approach to patent analytics in FinTech, offering a forward-looking tool to enhance innovation management and strategic IP planning.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"84 ","pages":"Article 102423"},"PeriodicalIF":1.9,"publicationDate":"2025-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840464","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 : 2025-12-08DOI: 10.1016/j.wpi.2025.102419
Jeong-sang Eom , Dong-chan Kim , Ji-hun Han , Won-Gyu Bae
Offshore wind energy is emerging as a pivotal energy resource, and as turbine dimensions expand to meet growing power demands, structural requirements for support towers have intensified. This has led to the use of thicker steel plates, introducing challenges such as microstructural inhomogeneity from uneven cooling across plate thicknesses. To address these issues, we conducted a comprehensive patent analysis on heavy steel plate technologies to identify technological gaps and track innovation trends. We developed a classification framework to organize production methods aimed at enhancing mechanical properties. Additionally, we assessed average steel plate thicknesses across countries and companies, reflecting the trend towards larger turbines and towers. Patent impact and market potential were evaluated using the Cites Per Patent (CPP) and Patent Family Size (PFS) indices.
{"title":"Enhancing mechanical performance of thick steel plates for offshore wind structures: A classification and patent landscape study","authors":"Jeong-sang Eom , Dong-chan Kim , Ji-hun Han , Won-Gyu Bae","doi":"10.1016/j.wpi.2025.102419","DOIUrl":"10.1016/j.wpi.2025.102419","url":null,"abstract":"<div><div>Offshore wind energy is emerging as a pivotal energy resource, and as turbine dimensions expand to meet growing power demands, structural requirements for support towers have intensified. This has led to the use of thicker steel plates, introducing challenges such as microstructural inhomogeneity from uneven cooling across plate thicknesses. To address these issues, we conducted a comprehensive patent analysis on heavy steel plate technologies to identify technological gaps and track innovation trends. We developed a classification framework to organize production methods aimed at enhancing mechanical properties. Additionally, we assessed average steel plate thicknesses across countries and companies, reflecting the trend towards larger turbines and towers. Patent impact and market potential were evaluated using the Cites Per Patent (CPP) and Patent Family Size (PFS) indices.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"84 ","pages":"Article 102419"},"PeriodicalIF":1.9,"publicationDate":"2025-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145738647","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 : 2025-12-05DOI: 10.1016/j.wpi.2025.102421
K.C. Pantoja , V.S. Tarabal , M.E.J. Oliveira , A.G.S. Oliveira , C.L.V. Silva , P.F. Nascimento , T.A. França , R.I.M.A. Ribeiro , J.A. Dernowsek , P.A. Granjeiro
Three-dimensional (3D) bioprinting is emerging as a high-complexity technology in the field of biofabrication, integrating interdisciplinary principles from engineering, materials science, cell biology, and regenerative medicine. This technique enables the fabrication of functional biological constructs composed of living cells and biomaterials through additive manufacturing methods with high spatial resolution. This article provides an in-depth analysis of the main applications, recent advances, and technical limitations related to 3D bioprinting, with emphasis on its implementation in bioprocesses. In the biomedical context, significant progress has been observed in tissue engineering and 3D disease modeling, particularly in translational oncology and the development of predictive drug screening platforms. In industrial biotechnology, bioprinting has been employed for the production of high-purity biological inputs, such as extracellular matrix (ECM) proteins, using human cell systems, thereby promoting more sustainable, animal-free production routes. In the food industry, this technology allows the development of personalized and nutritionally tailored products incorporating innovative and environmentally sustainable ingredients, such as microalgae and insects. In the agricultural sector, 3D bioprinting has been applied to plant tissue engineering and the design of biomimetic models to optimize crop systems. Additionally, a patentometric analysis highlights the global expansion of 3D bioprinting, with a notable increase in filings across international jurisdictions and a gradual transition toward technological maturity. The findings underscore the strategic role of 3D bioprinting as a driver of technological innovation with significant impacts on health, sustainability, and the bioeconomy.
{"title":"Global patent panorama of 3D bioprinting: Trends, maturity and key stakeholders","authors":"K.C. Pantoja , V.S. Tarabal , M.E.J. Oliveira , A.G.S. Oliveira , C.L.V. Silva , P.F. Nascimento , T.A. França , R.I.M.A. Ribeiro , J.A. Dernowsek , P.A. Granjeiro","doi":"10.1016/j.wpi.2025.102421","DOIUrl":"10.1016/j.wpi.2025.102421","url":null,"abstract":"<div><div>Three-dimensional (3D) bioprinting is emerging as a high-complexity technology in the field of biofabrication, integrating interdisciplinary principles from engineering, materials science, cell biology, and regenerative medicine. This technique enables the fabrication of functional biological constructs composed of living cells and biomaterials through additive manufacturing methods with high spatial resolution. This article provides an in-depth analysis of the main applications, recent advances, and technical limitations related to 3D bioprinting, with emphasis on its implementation in bioprocesses. In the biomedical context, significant progress has been observed in tissue engineering and 3D disease modeling, particularly in translational oncology and the development of predictive drug screening platforms. In industrial biotechnology, bioprinting has been employed for the production of high-purity biological inputs, such as extracellular matrix (ECM) proteins, using human cell systems, thereby promoting more sustainable, animal-free production routes. In the food industry, this technology allows the development of personalized and nutritionally tailored products incorporating innovative and environmentally sustainable ingredients, such as microalgae and insects. In the agricultural sector, 3D bioprinting has been applied to plant tissue engineering and the design of biomimetic models to optimize crop systems. Additionally, a patentometric analysis highlights the global expansion of 3D bioprinting, with a notable increase in filings across international jurisdictions and a gradual transition toward technological maturity. The findings underscore the strategic role of 3D bioprinting as a driver of technological innovation with significant impacts on health, sustainability, and the bioeconomy.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"84 ","pages":"Article 102421"},"PeriodicalIF":1.9,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685720","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 : 2025-12-05DOI: 10.1016/j.wpi.2025.102422
Hady M. Khawand , Markus Kittler , Elie Chahda
This study assesses the level of intellectual property (IP) awareness among top executives in small and medium-sized enterprises (SMEs) within the Gulf Cooperation Council (GCC) region. It addresses a notable gap in the literature on IP familiarity and its strategic use in emerging markets. We surveyed 526 executives across the six GCC states, with scales developed to measure IP familiarity, perception of IP's importance, and understanding of central IP concepts (trademarks, patents, copyrights). Statistical analysis reveals a significant lack of IP awareness, particularly in fundamental areas like patent protection and territorial limitations, underscoring potential risks to strategic decision-making and growth. The findings demonstrate a strong, positive correlation between participation in IP-related education and familiarity with IP concepts, yet most executives lack practical understanding of IP's strategic value. Tailored IP education—through workshops, university courses, and industry conferences—is recommended to bridge this gap, aligning executive knowledge with international standards and fostering an innovation-driven business environment in the GCC.
{"title":"Intellectual property awareness in the Gulf region","authors":"Hady M. Khawand , Markus Kittler , Elie Chahda","doi":"10.1016/j.wpi.2025.102422","DOIUrl":"10.1016/j.wpi.2025.102422","url":null,"abstract":"<div><div>This study assesses the level of intellectual property (IP) awareness among top executives in small and medium-sized enterprises (SMEs) within the Gulf Cooperation Council (GCC) region. It addresses a notable gap in the literature on IP familiarity and its strategic use in emerging markets. We surveyed 526 executives across the six GCC states, with scales developed to measure IP familiarity, perception of IP's importance, and understanding of central IP concepts (trademarks, patents, copyrights). Statistical analysis reveals a significant lack of IP awareness, particularly in fundamental areas like patent protection and territorial limitations, underscoring potential risks to strategic decision-making and growth. The findings demonstrate a strong, positive correlation between participation in IP-related education and familiarity with IP concepts, yet most executives lack practical understanding of IP's strategic value. Tailored IP education—through workshops, university courses, and industry conferences—is recommended to bridge this gap, aligning executive knowledge with international standards and fostering an innovation-driven business environment in the GCC.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"84 ","pages":"Article 102422"},"PeriodicalIF":1.9,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145685721","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 : 2025-12-04DOI: 10.1016/j.wpi.2025.102420
Joe Waterstraat, Lothar Walter
Patent searches support innovation, legal compliance, and business decisions, but are often complicated by extensive data, diverse systems and linguistic challenges. This paper presents a multi-perspective, keyword-based approach drawing on design theory to address the ‘fuzzy’ nature of complex technology fields. Using the example of Nursing Care Technology (NCT), an interdisciplinary domain lacking a specific patent classification, we develop three search strategies reflecting the perspectives of designers, users, and systems.
In order to measure the effectiveness of each search perspective in identifying relevant documents, we use a Large Language Model (LLM) to assess the precision of the respective results, including their subsets and intersections. Patents identified from all three design-theory perspectives have the highest precision, suggesting that the combination of viewpoints helps to isolate core innovations. Our analysis of patent classifications and assignees also demonstrates the value of the method for exploring ‘fuzzy’ technology fields.
By adapting design theory to keyword-based patent searches and using an LLM to assess the precision of tailored search results, we advance both the theory and practice of patent information retrieval. This is especially useful for ‘fuzzy’ technology fields where conventional search methods often fall short.
{"title":"Designing tailored patent search approaches – A case study on nursing care technology","authors":"Joe Waterstraat, Lothar Walter","doi":"10.1016/j.wpi.2025.102420","DOIUrl":"10.1016/j.wpi.2025.102420","url":null,"abstract":"<div><div>Patent searches support innovation, legal compliance, and business decisions, but are often complicated by extensive data, diverse systems and linguistic challenges. This paper presents a multi-perspective, keyword-based approach drawing on design theory to address the ‘fuzzy’ nature of complex technology fields. Using the example of Nursing Care Technology (NCT), an interdisciplinary domain lacking a specific patent classification, we develop three search strategies reflecting the perspectives of designers, users, and systems.</div><div>In order to measure the effectiveness of each search perspective in identifying relevant documents, we use a Large Language Model (LLM) to assess the precision of the respective results, including their subsets and intersections. Patents identified from all three design-theory perspectives have the highest precision, suggesting that the combination of viewpoints helps to isolate core innovations. Our analysis of patent classifications and assignees also demonstrates the value of the method for exploring ‘fuzzy’ technology fields.</div><div>By adapting design theory to keyword-based patent searches and using an LLM to assess the precision of tailored search results, we advance both the theory and practice of patent information retrieval. This is especially useful for ‘fuzzy’ technology fields where conventional search methods often fall short.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"84 ","pages":"Article 102420"},"PeriodicalIF":1.9,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145658455","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 : 2025-11-14DOI: 10.1016/j.wpi.2025.102410
Amy J.C. Trappey , Yuga Y.C. Lin , Chun-Yi Wu
The substantial increase in patent applications has created notable challenges in retrieving, analyzing, and managing patent data. According to the World Intellectual Property Indicators (WIPI) report published by the World Intellectual Property Organization (WIPO) in 2024, the total number of patent applications worldwide surpassed 3.55 million in 2023. Traditional manual methods for extracting and interpreting key patented knowledge are usually time-consuming, expensive, subjective, and lack validation. To address the rise in patent filings and the growing need for effective patent knowledge management, we have developed an intelligent patent summarization system that utilizes large language model (LLM) technology to enhance the understanding and usability of patent documents. This research uses patents related to advanced vehicle-to-everything (V2X) technologies as case studies. Through empirical analysis, we show that the system can automatically condense large amounts of patent documents into concise and meaningful summaries. This intelligent patent summarization system runs efficiently on consumer-grade computers. Experimental results indicate that its semantic structure achieves nearly 90 % similarity compared to patents written by domain experts. This research aims to enhance the efficiency, accuracy, and accessibility of patent document processing, thereby significantly advancing the practical application of this technology.
{"title":"Generative AI-based intelligent patent summarization for intellectual property knowledge communication and cooperation","authors":"Amy J.C. Trappey , Yuga Y.C. Lin , Chun-Yi Wu","doi":"10.1016/j.wpi.2025.102410","DOIUrl":"10.1016/j.wpi.2025.102410","url":null,"abstract":"<div><div>The substantial increase in patent applications has created notable challenges in retrieving, analyzing, and managing patent data. According to the World Intellectual Property Indicators (WIPI) report published by the World Intellectual Property Organization (WIPO) in 2024, the total number of patent applications worldwide surpassed 3.55 million in 2023. Traditional manual methods for extracting and interpreting key patented knowledge are usually time-consuming, expensive, subjective, and lack validation. To address the rise in patent filings and the growing need for effective patent knowledge management, we have developed an intelligent patent summarization system that utilizes large language model (LLM) technology to enhance the understanding and usability of patent documents. This research uses patents related to advanced vehicle-to-everything (V2X) technologies as case studies. Through empirical analysis, we show that the system can automatically condense large amounts of patent documents into concise and meaningful summaries. This intelligent patent summarization system runs efficiently on consumer-grade computers. Experimental results indicate that its semantic structure achieves nearly 90 % similarity compared to patents written by domain experts. This research aims to enhance the efficiency, accuracy, and accessibility of patent document processing, thereby significantly advancing the practical application of this technology.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"83 ","pages":"Article 102410"},"PeriodicalIF":1.9,"publicationDate":"2025-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528012","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 : 2025-11-13DOI: 10.1016/j.wpi.2025.102411
Ioannis Pontikis, Chen Li, Dimitrios Chrysostomou
Patent retrieval often faces unique challenges due to the complex structure and nature of technical documents. Traditional similarity measures often fail to capture the nuanced semantic relationships between inventions, marking it difficult for non-experts to retrieve relevant prior art. This study introduces a novel eigenvector-based ranking methodology for patent similarity that significantly outperforms traditional embedding approaches. We integrate covariance-matrix analysis with hyperplane projections, to capture both semantic and structural relationships between technical documents. Experiments within the F03D patent subclass demonstrate our approach achieves a similarity score of 83.37, substantially outperforming Word2Vec (23.3), ELMo (21.1), and SimCSE (44.8). This work addresses critical challenges in patent retrieval while introducing innovations applicable to broader technical document similarity tasks, enabling non-experts to efficiently identify relevant prior work without specialized knowledge of patent systems.
{"title":"EigenPatent: A novel eigenvector-based ranking method for enhanced patent similarity detection","authors":"Ioannis Pontikis, Chen Li, Dimitrios Chrysostomou","doi":"10.1016/j.wpi.2025.102411","DOIUrl":"10.1016/j.wpi.2025.102411","url":null,"abstract":"<div><div>Patent retrieval often faces unique challenges due to the complex structure and nature of technical documents. Traditional similarity measures often fail to capture the nuanced semantic relationships between inventions, marking it difficult for non-experts to retrieve relevant prior art. This study introduces a novel eigenvector-based ranking methodology for patent similarity that significantly outperforms traditional embedding approaches. We integrate covariance-matrix analysis with hyperplane projections, to capture both semantic and structural relationships between technical documents. Experiments within the F03D patent subclass demonstrate our approach achieves a similarity score of 83.37, substantially outperforming Word2Vec (23.3), ELMo (21.1), and SimCSE (44.8). This work addresses critical challenges in patent retrieval while introducing innovations applicable to broader technical document similarity tasks, enabling non-experts to efficiently identify relevant prior work without specialized knowledge of patent systems.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"83 ","pages":"Article 102411"},"PeriodicalIF":1.9,"publicationDate":"2025-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145528013","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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