World Patent Information最新文献

{"title":"Patent status of biodegradable polymers and identification of new application areas by IPC network analysis","authors":"Cheol-Ju Lee ,&nbsp;Hyoung Ryul Ma ,&nbsp;Young-Teck Kim","doi":"10.1016/j.wpi.2024.102298","DOIUrl":"10.1016/j.wpi.2024.102298","url":null,"abstract":"<div><p>Biodegradable polymers (BDPs), due to their degradability, have great merits for applications in the environmental fields compared to conventional polymers. Furthermore, they are recently receiving renewed attention with the rise of globally issued environmental problems caused by plastic wastes. However, BDPs are still produced and utilized with limited amounts and applications in comparison to conventional plastics. To help expand the application area of BDPs, we mainly focus on the emerging and exotic technologies of BDPs by analyzing International Patent Classification (IPC) co-classification networks constructed from 2,862 patents on BDPs filed with the US Patent and Trademark Office from 2006 to 2022. As a result, by detecting both recently appearing and isolated IPCs, new and relatively unknown application areas of BDPs such as animal trap, polishing composition, rope lubricant, underground structure, ammunition, digital data carrier are identified. Our IPC analysis methodology studied in the field of BDPs would be also useful for researchers and entrepreneurs searching new and emerging applications in various technology areas.</p></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"78 ","pages":"Article 102298"},"PeriodicalIF":2.2,"publicationDate":"2024-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141732306","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}

{"title":"Forecasting patenting areas with academic paper & patent data: A wind power energy case","authors":"Chih-Hung Hsieh ,&nbsp;Chien-Huei Lin ,&nbsp;Louis Y.Y. Lu ,&nbsp;Angel Contreras Cruz ,&nbsp;Tugrul Daim","doi":"10.1016/j.wpi.2024.102297","DOIUrl":"10.1016/j.wpi.2024.102297","url":null,"abstract":"<div><p>This study proposes a novel method to forecast the emerging patenting area with Main Path Analysis and Word Cloud Analysis. To test the methods, we used Wind Power Energy as an example to illustrate the method's usefulness. Firstly, we used “wind power” and “wind energy” to collect 40,827 related journal papers in Scopus and 72,979 related patents in Derwent Innovation databases. Main Path Analysis was conducted to explore the development trajectory. The results of the Main Path Analysis for the papers and patents were visualized with Pajek software. Secondly, we used VOSviewer to extract the technological areas (i.e., keywords) of the collected academic papers and patents. Then, we calculated the average time lag between the first paper published and the first patent filed for each technological area (keyword). Finally, we forecasted the trend of patenting for wind power energy based on the average lag time and academic research themes in recent years.</p></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"78 ","pages":"Article 102297"},"PeriodicalIF":2.2,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141729426","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}

{"title":"Identifying core IoT technologies using ARM and FCM: A comprehensive data-driven method","authors":"Jalil Heidary Dahooie ,&nbsp;Iman nouri ,&nbsp;Mehdi Mohammadi ,&nbsp;Haydar Yalcin ,&nbsp;Tugrul Daim","doi":"10.1016/j.wpi.2024.102295","DOIUrl":"10.1016/j.wpi.2024.102295","url":null,"abstract":"<div><p>The internet of things (IoT) technology has garnered significant attention in recent years due to its wide-ranging applications. IoT, with its high connectivity capabilities, integrates various industrial, domestic, and agricultural devices into a smart and remotely controllable software and hardware platform. The field of IoT technology is expansive and encompasses a multitude of sub-technologies. Identifying core technologies in this domain is crucial for guiding research and development efforts by companies. Given the interrelation of these core technologies and their combination with recent decision-making approaches, network-based strategies have recently received special attention. The developed methods are based on static conditions and the assumption of stability, while in emerging technologies like IoT, the pace of changes over time is high. This leads to changes in the importance of technologies under various scenarios.</p><p>In this study, in order to analyze the extracted patent data, association rule mining (ARM) algorithms were applied to identify the relationships between technologies and social network analysis was used to analyze the relationships between technologies and estimate their initial weights. Finally, fuzzy cognitive map (FCM) were used to estimate the final weights of technologies and rank them. The fcm approach allows for simultaneous modeling of both static and dynamic states of the system and, on the other hand, by calculating under various scenarios, suggests a core technology that is sustainable.</p><p>The research results show that digital information transmission technologies, digital or electrical data processing, and wireless communication networks are the most important sub-technologies of Internet of things.</p></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"78 ","pages":"Article 102295"},"PeriodicalIF":2.2,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141639382","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}

{"title":"Will AI solve the patent classification problem?","authors":"Eleni Kamateri ,&nbsp;Michail Salampasis ,&nbsp;Eduardo Perez-Molina","doi":"10.1016/j.wpi.2024.102294","DOIUrl":"https://doi.org/10.1016/j.wpi.2024.102294","url":null,"abstract":"<div><p>This paper scrutinizes the act of patent classification as it is performed by specialists, namely patent examiners, and currently supported by automated systems in patent offices for assigning classification codes to patent application documents. It collectively discusses aspects of the patent classification operation, some of them not very visible, which are not commonly encountered in other document and text classification tasks. The advent of Deep Learning (DL) and, especially, Large Language Models (LLMs) offer a new perspective on the development of automated systems addressing these inherent aspects of patent classification. Towards this direction, the paper analyses how these technologies can address the patent classification problems and concludes with a discussion of potential challenges and benefits that the application of Artificial Intelligence (AI) technologies may bring to the task of patent classification.</p></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"78 ","pages":"Article 102294"},"PeriodicalIF":2.2,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141605311","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}

{"title":"Patent characteristics for leishmaniasis treatment as a basis for freedom-to-operate analysis","authors":"Cristian Buendia-Atencio ,&nbsp;Solange Alexandra Arévalo Bello ,&nbsp;Anny Rodríguez ,&nbsp;Vaneza Paola Lorett Velasquéz ,&nbsp;Laura Cuervo ,&nbsp;Mónica Losada-Barragán ,&nbsp;Silvio Alejandro Lopez-Pazos","doi":"10.1016/j.wpi.2024.102296","DOIUrl":"https://doi.org/10.1016/j.wpi.2024.102296","url":null,"abstract":"<div><p>Among the main zoonoses with the highest morbidity burden is leishmaniasis. The parasite of the genus <em>Leishmania</em> is its etiological agent. There are three forms of the disease: cutaneous, mucocutaneous and visceral. Pentavalent antimonial drugs are used for leishmaniasis treatment, however toxic side effects and parasite resistance have been detected. Intellectual Property Rights (IPRs) protect inventions that promote benefits to society, and patents are particularly notable for preserving advancements in biotechnology. To introduce innovative technologies, it is necessary to analyze the elements and processes involved in the development of products that may be protected by IPRs. This process consists of product deconstruction into its elements for an intellectual property analysis to contemplate commercial viability, and to determine strategies to avoid infringing third party rights (Freedom-to-Operate approach). In this project, a sample of patents protecting treatments directed against leishmaniasis were evaluated in order to know their characteristics, and to establish useful elements for Freedom-to-operate strategies. Open access patent databases were used (The Lens, Google patents, Patentscope, among others), and relevant characteristics such as claims, owners, technology protection region, or year of application for protection were determined. The sample obtained includes patents from 1967 to 2023. The majority of patents were found to be located in countries such as Brazil or the United States, and described developments focused on compounds derived from chemical synthesis, polypeptides, extracts, antigens, or structural components of the parasite. There are several patents that have already expired and whose information can be freely used. The Bolar exemption would allow the use of information from these patents for regulatory compliance purposes. This study provides an overview of what has been patented for leishmaniasis treatment, and information on Freedom-to-operate focus.</p></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"78 ","pages":"Article 102296"},"PeriodicalIF":2.2,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141605310","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}

{"title":"Literature listing","authors":"Susan Bates","doi":"10.1016/j.wpi.2024.102284","DOIUrl":"https://doi.org/10.1016/j.wpi.2024.102284","url":null,"abstract":"<div><p>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 &amp; Certification; and Legal &amp; Intellectual Property Office Matters. The current Literature Listing was compiled end-May 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.</p></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"78 ","pages":"Article 102284"},"PeriodicalIF":2.7,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141322853","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}

{"title":"Modeling an indicator for statutory patent novelty","authors":"Valentin J. Schmitt,&nbsp;Nils M. Denter","doi":"10.1016/j.wpi.2024.102283","DOIUrl":"https://doi.org/10.1016/j.wpi.2024.102283","url":null,"abstract":"<div><p>Novelty is considered a <em>conditio sine qua non</em> for the grant of a patent by most relevant patent authorities and in U.S. patent law defined by 35 U S C. §102. Previous attempts to operationalize patent novelty have been mostly based on theoretical principles, such as recombination theory, and have not estimated novelty according to data that officially determines whether sufficient novelty is present in an application. To overcome this gap, this study analyzes whether established measures of patent novelty are capable of predicting the rejection of an application based on lack of novelty. Furthermore, this study applies a combination of sophisticated unsupervised and supervised machine learning techniques to patent data and provides the possibility to estimate statutory novelty practiced by the USPTO by a modeled indicator. Measuring such statutory novelty would give applicants a tremendous competitive advantage to pursue patent strategies offensively and/or defensively. For example, the indicator allows companies – particularly small and medium-sized companies with limited resources – to assess the novelty and therefore the patentability of one’s own invention. Large companies, most of which are more likely to pursue an offensive patent strategy, can use the indicator to measure the novelty of numerous published third-party patents and challenge their validity.</p></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"78 ","pages":"Article 102283"},"PeriodicalIF":2.7,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141240674","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}

{"title":"A novel re-ranking architecture for patent search","authors":"Vasileios Stamatis,&nbsp;Michail Salampasis,&nbsp;Konstantinos Diamantaras","doi":"10.1016/j.wpi.2024.102282","DOIUrl":"10.1016/j.wpi.2024.102282","url":null,"abstract":"<div><p>Patent search presents unique challenges due to the intricate structure and specialized terminology embedded in patent documents. While neural models have been successfully applied in various information retrieval (IR) tasks, these inherent complexities have hindered their effectiveness in patent search. To address these challenges, we propose a novel re-ranking architecture that effectively handles long, structured patent documents and leverages AI models to interpolate lexical and semantic signals of relevance. Additionally, the architecture incorporates query-specific weights for the final re-ranking process. To address partial relevance between patent sections our method effectively models the relevance relationships between different sections of patent documents. We calculate lexical and semantic signals of relevance from each document section and feed them as input features to AI models that estimate a combined relevance score. Finally, we compute query-specific weights to determine the relative contributions of lexical and semantic relevance for the final re-ranking. Extensive experiments on the CLEF-IP dataset demonstrate that our method outperforms several baselines, achieving substantial and statistically significant improvements in retrieval performance. We further assess the adaptability of our method using the MSMARCO dataset, where it exhibits limited performance, indicating its suitability for domain-specific patent research.</p></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"78 ","pages":"Article 102282"},"PeriodicalIF":2.7,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141187865","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}

{"title":"Trust in information security technology: An intellectual property analysis","authors":"Angélica Pigola ,&nbsp;Fernando de Souza Meirelles ,&nbsp;Priscila Rezende da Costa ,&nbsp;Geciane Silveira Porto","doi":"10.1016/j.wpi.2024.102281","DOIUrl":"https://doi.org/10.1016/j.wpi.2024.102281","url":null,"abstract":"<div><p>While zero-trust (ZT) technologies cover many aspects of trust in information security (TinIS) critical to Federal enterprises, more research is required to effectively identify their benefits at scale. In this sense, an appropriate valuation of ZT intellectual property (IP) uncovers future challenges with ZT principles to both scholars and Federal enterprises. Therefore, this research attempts to understand the marginal effects of having ZT IP on Federal enterprise governance in terms of return on government effectiveness, regulatory quality, and e-participation. We collected objective data from Derwent Innovation (Clarivate Analytics) and the World Intellectual Property Organization (WIPO IP Statistics) to test the interplay of the 1297 ZT strategic patent with Federal enterprise governance. Through panel regression models using fixed effects, we conduct Heckman correction model analyses and the generalized moment method (GMM) to alleviate potential sampling biases and endogeneity. The findings suggest that ZT strategic patent is positively related to both government effectiveness and regulatory quality but without any effect on e-participation. Furthermore, we find that diverse technological IP portfolios in ZT technologies do not strengthen the effects of ZT strategic patent on Federal enterprises.</p></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"78 ","pages":"Article 102281"},"PeriodicalIF":2.7,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141094913","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}

{"title":"Estimating patent value in the United States and Japan","authors":"Masami Kawase","doi":"10.1016/j.wpi.2024.102280","DOIUrl":"https://doi.org/10.1016/j.wpi.2024.102280","url":null,"abstract":"<div><p>Patents contribute to economic development; therefore, estimations of patent value are significant in measuring their impact on the economy. With this in mind, this article discusses estimations of patent value with the renewal model developed by several economists. Targeted patents are those issued in the United States and Japan from 1990 to 2010. In addition, the study examines patent values for several technology fields and considers which technology field should be the focus for the United States and Japan. Moreover, this article compares estimations based on the renewal model versus those based on other data such as sales, trade prices, or trials and analyzes how close this model's estimations are to the real values. This article's results demonstrate that the renewal model is useful for evaluating patents overall and analyzing technological trends from a patent perspective.</p></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"77 ","pages":"Article 102280"},"PeriodicalIF":2.7,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141072603","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}