World Patent Information最新文献

By their nature, patents allow for the protection of creations or inventions in various technological sectors and in countries of commercial or industrial interest. They also record information about inventors and holders, as well as the novel features of the invention. With this in mind, this article considers the contributions of Colombians in the global context by analyzing patent applications submitted between 2000 and 2019 in jurisdictions other than their own.

The research focused on the analysis of patent application records obtained from the World Intellectual Property Organization (WIPO) patent database, in which at least one Colombian was listed as a holder. The results show that while the number of applications was not very high, they were distributed across various technological areas and were primarily filed in Europe, North America, and Asia, with minimal participation in Central and South America. Analysis also revealed a high level of collaboration, with 69% of the applications filed jointly. Additionally, 84% of the holders associated with the records obtained are natural persons.

Probing the development of technology can offer insights into its future implementation. In this study, patent statistics are used to examine the changes in the technological capacity of the telecommunication sector in China and shed light on the development of 5G technology. Given full access to patent data, we find an increase in patent applications eventually leads to an increase in the innovation quality of the Chinese telecommunication sector. Firms, particularly industry leaders, greatly contribute to technological capacity by constantly producing high-quality innovation. Unlike those of previous studies, our findings reveal that a robust advancement reduces the technological capacity gap between the telecommunication sectors of the U.S. and China. Patent measures not only enable us to determine that Chinese telecommunication technology is at the gradual catch-up stage of the catch-up cycle, but also reveal responses to the technology window, the demand window, and the institutional windows of opportunity. Moreover, patent statistics can track knowledge flows. It can also find that accessing foreign knowledge has helped the Chinese telecommunication sector for learning and assimilating such knowledge to cultivate its knowledge base. We further find other than training qualified professionals, universities offer limited contributions to the technological capacity of the telecommunication sector.

The lifetime of a patent is 20 years, but many patents get abandoned before completing this duration. This may be in part due to the high maintenance fee required by United States Patent and Trademark Office (USPTO), lack of demand for licensing, limited scope for workability in dynamic market situation, deficit of investment in taking it forward, change in the priorities of the inventor or emergence of more affordable or frugal competitive products. We have created a knowledge repository of abandoned patents in USPTO which are available for use by the scholars, entrepreneurs and others in the society. This repository has additional open access features compared to the earlier repository by Pearce such as the names of inventors, the country of inventors, date of abandonment along with the status of the patents, assignee history, number of citations, CPC, NBER and WIPO categories of each patent and entity status.

In this paper we have analyzed some trends in the rate of abandonment over the years vis a vis non-abandoned or active patents over the years. We have also explored the number of abandoned and non-abandoned patents in different sectors based on the Cooperative Patent Classification (CPC) of patents. We have created a framework to classify the patents into separate categories based on the filing and abandonment rate. We have taken forward the work on patent lifecycle and used it to understand lifecycle of patent sectors. We have also created a quantitative metric, called as obsolescence rate, to identify the rising and declining sectors. Based on the obsolescence rate, sectors such as Heterocyclic Compounds (CPC category: C07D); Information Storage Based On Relative Movement Between Record Carrier And Transducer (CPC category: G11B); and Apparatus For Physical Training, Gymnastics, Swimming, Climbing, Or Fencing; Ball Games; Training Equipment (CPC category: A63B) and which are to the right of the reference line have a higher obsolescence rate and are hence declining sectors. Similarly, categories such as Computer Systems Based On Specific Computational Models (CPC category: G06 N); Systems For Controlling Or Regulating Non-Electric Variables (CPC category: G05D); and Control Or Regulating Systems In General; Functional Elements Of Such Systems; Monitoring Or Testing Arrangements For Such Systems Or Elements (CPC category: G05B) are on the left of reference line and are hence the rising sectors.

Wind energy patents are conventionally defined using Cooperative Patent Classification (CPC) and International Patent Classification (IPC) codes that represent wind motors (F03D) and wind energy (Y02E 10/70). This study examines whether these codes sufficiently represent the wind energy patent domain. Using a combination of keywords and classification codes identified through expert input and manual review, we construct an expanded domain with a 7.5% increase in patent count, a 6% increase in recall, and only a 1% decrease in precision for wind energy patents. We also found that the conventional domain is not unbiased; it underrepresents patenting from China and patents published since 2010. This is important because an improved patent domain allows for a holistic patent data set, which is necessary to complete a thorough analysis of the wind industry. Through this wind energy application, we extend our methodology to form a generalized patent search process that can be used to target technology domains within a patent data set.

A deep learning-based method was developed to retrieve and analyze patents related to green sciences in cosmetics. An exploratory phase was conducted with five transformer machine learning models on a training set to screen out the most relevant one. A second phase was implemented to fine-tune the selected model by comparing the results generated by the algorithm to the manual scoring done by an expert on a naive set of data. The final model is based on a combination of BERT-like and Longformers models which successively analyze the abstract, the description and the first claim of each patent. A survey of the patent literature with the selected model shows that key information can be obtained regarding the patenting activity in green sciences in cosmetics.

The rapid development of information technology, along with advanced wireless communication technologies, has revolutionized the use of unmanned aerial vehicles (UAVs or drones) in many industries. In agriculture, due to the climate change and the growing global population, causing unprecedented demands and risks on food supplies, intelligent and automatic agricultural technologies are critical needs. UAVs offer a wide range of applications to transform traditional agricultural practices into Agriculture 4.0 that integrates advanced technology to optimize agricultural productivity, sustainability, and efficiency. To gain comprehensive insights into the current and future development of agricultural UAVs technologies, this research conducts extensive review and analysis of patents and non-patent literature in the field. By thoroughly examining the literature, the knowledge ontology of ag-UAV technologies is presented. Additionally, comprehensive macro- and micro-patent analyses identify the patenting trends and top tech-leaders for the key technologies related to agricultural drones. Moreover, utilizing regression modeling, technology maturity analysis, and technology-function matrix (TFM), the current and future R&D trends and the cold and hot spots of the technical innovations are identified. Through these detailed patent analyses, the state-of-the-art and potential advancements in agricultural UAV technologies are depicted, serving as crucial intelligence for R&D initiatives and IP strategies.

We suggest key performance indicators (KPIs) that provide a systematic framework to analyse the functioning of utility model (UM) systems. The KPIs are based on a literature review and a content analysis of the webpages of IP offices in countries offering UM protection in 2021. Generally, the IP offices highlight UMs to be shorter, simpler, faster, and cheaper protection methods compared to patents but there are differences how these features are highlighted. The differences between UMs and patents lead to multidimensional sorting as economic agents choose within the IP menu which determine the observed differences in characteristics and outcomes of patents and UMs. National differences call for separate context-dependent KPIs for UM systems.