Technological developments in nanomaterials can be tracked using patent indicators. However, the traditional International Patent Classification indicators cannot be considered conclusive, since nanotechnology is not easily defined as a field of research as well as there are different types of nanomaterials not well delineated into hierarchical codes. Therefore, text mining approaches can be used to enhance patent analysis and provide insightful trends to support research and development, competitive intelligence, and policy making. This study aims at proposing a method to classify nanomaterials into main types and mapping technological developments using an advanced text mining-based method to compile patent indicators. Patent records were provided by Derwent Innovations Index database, which indexes an enhanced bibliographic data of patents filed worldwide. A comparison between the IPC indicators and those developed here by text mining is presented. We concluded that the proposed method provides useful outcomes for decision-making, technological forecasting, and material selection process.
Author(s): Douglas Henrique Milanez, Leandro Innocentini Lopes de Faria, Daniel Rodrigo Leiva
Organization(s): Federal University of São Carlos
Source: Journal of Nanoparticle Research
The purpose of this paper is to effectively evaluate the innovation ability and classification of technical talents in the intelligent robot field, and to be able to carry out adaptive learning and mining technical innovation talents according to the real-time change data corresponding to different indicators. Taking inventor’s patent information retrieved and cleaned from DI database as research object, it constructs the evaluation index system of technological innovation talents. It reduces the dimension of the index and cluster automatically, shows the visual effect, and mines the similar technical innovation talents through t-SNE algorithm. For a large number of patent information data, machine learning algorithm improves the traditional recognition method. According to inventor similarity, automatic classification is realized. Combined with DWPI manual code mining, the corresponding innovators and members of the technical team in the intelligent robot technology field were found. According to the results of visual dimensional reduction, the specific inventors can be traced. Machine learning algorithm t-SNE can reduce dimension and analysis clustering. It breaks the limitations of artificial statistics, deals with the larger order of magnitude data, and analyzes data timely, accurate and intuitive.
Author(s): Ning Zhao, Guohui Yang, Yang Cao
Organization(s): Harbin Institute of Technology
Source: 2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)
Quantum technologies attracted much attention for their disruptive potential in last two decades. The article analyzes the worldwide patent landscape for quantum technologies based on data extracted from Derwent Innovation and Web of Science. The quantum technologies were grouped
into three distinct technology areas of quantum computing, quantum communication and quantum sensing, to demonstrate detailed development and trends respectively. It shows that quantum technology is a highly competitive research field, and United States, China and Japan are the most prominent countries, in particular China made a great progress in recent years. United States has a significant advantage in the field of quantum computing, which is the most promising field, meanwhile China has a significant advantage in the field of quantum communication and succeeds in launching a quantum satellite.
Author(s): Juan Zhang, Qianfei Tian, Chuan Tang, Lina Wang, Jing Xu, and Junmin Fang
Organization(s): Chengdu Library and Information Center
Source: International Journal of Information and Education Technology
This work aims to analyse a relational structure of patents in automotive sector, especially for electric vehicles. The automotive industry is equivalent to 22% of Brazil’s industrial gross domestic product (GDP), 4% of Brazil’s total GDP, and worldwide it should reach a mark of 100 million vehicles sold by 2020. In recent decades, innovation processes have become a matter of survival for companies. Resource Based View admits that companies are looking for strategic resources that are a source of competitive advantage. This work comprises the automotive market as an organizational field in which the actors struggle to reach more favourable positions from the available resources. The network approach was used together with patent analysis to highlight the existing relationships within this industry in the construction of innovation, through the analysis of patents of high commercial value in the automotive sector, collected through the Derwent database.
For FULL-TEXT see http://leblog.gerpisa.org/node/4456
Author: Filippo Filippo Savoi de Assis
Organization: Universidade Federal de São Carlos – UFSCar
Source: Gerpisa Colloquium
As technological innovation plays important role in today’s knowledge economy, intellectual property as the most important output of technological development is valued highly for generating monopoly position in providing payoffs to innovation. Intellectual Property Management (IPM) helps organizations to identify, enhance and evaluate their technological strength. Patent portfolio Model (PPM) is built for assessing the advantages and disadvantages of organization, identifying the opportunities of development potentials and optimal distribution, to support the decision-making for optimizing resource allocation and developing layout for technical field. The case study of research institute in china show that this method is feasible and fulfilled the needs of different institutions, so as to provide suggestions for R&D technology management.
Author(s): Li Shuyin, Zhang Xian, Xu Haiyun, Fang Shu
Organization(s): Chengdu Library and Information Center, Chinese Academy of Sciences
Source: IEEE Xplore: 2019 Portland International Conference on Management of Engineering and Technology (PICMET)
3D printing technology has already been created by the manufacturing industry for decades. In the health area has grown rapidly, allowing the application to various areas of medicine. This work carried out a quantitative study in patent databases with the aim of sticking to the innovations that emerged with the 3D printer applied to health through technological indicators inherent in patents. It is possible to check the countries, companies and applications for the innovations that emerged after the patent for Fusion and Deposition Modeling (FDM) technology came into the public domain. China, listed as one of the countries in the Global Innovation Index, holds the development of new technologies as well as the patent protection of 3D Health Printer prototypes.
A tecnologia da impressão 3D tem sido utilizada pela indústria de manufatura há décadas. Na área da saúde tem crescido rapidamente, possibilitando a aplicação em diversas áreas da medicina. Este trabalho realizou um estudo quantitativo nas bases de dados de patentes com o objetivo de apontar as inovações surgidas com a impressora 3D aplicada à saúde por meio de indicadores tecnológicos inerentes nas patentes. É possível verificar os países, as empresas e as aplicações referentes às inovações que surgiram após a patente da tecnologia de Modelagem por Fusão e Deposição (FDM) entrar em domínio público. A China, listada como um dos países no Índice Global de Inovação, detém o desenvolvimento de novas tecnologias, bem como a proteção por patente de protótipos da Impressora 3D aplicado à saúde.
D.O.I.: 10.7198/geintec.v9i4.1413 Full-Text at link below
Technological Innovations of the 3D printer applied to health
Author(s): Lana Grasiela Alves Marques, Rosângela Cordeiro de Souza Assef Neto, Rosane Abdala Lins, Maria Cristina Soares Guimarães
Organization(s): Fundação Oswaldo Cruz – FIOCRUZ
As a basic tool for technology evolution analysis, technology network can visualize the relationship among technologies in different patents. However, the current constructions of technology network only represent common technical information, and cannot reflect different types of technical information. We propose a new approach to construct a fine-grained technology network and display technical information from multiple perspectives. Based on the Subject-Action-Object (SAO) structures extracted from patent documents, we first classify the technical information, and then investigate the semantic relationship among different types of technical information. Based on that, single-type and multi-type technology networks are constructed, which can demonstrate different types of technical information and make the technology evolution analysis easier and more reliable. Finally, taking the Nano-fertilizer patents as a data source, we construct a fine-grained construction of technology network, which might help identify fundamental and emerging technologies in the Nano-fertilizer field.
Author(s): Xiaoman Li, Hongyan Song, Xuefu Zhang, Qian Xu
Organization: Agricultural Information Institute, Chinese Academy of Agricultural Sciences
Source: Proceedings of the 3rd International Conference on Computer Science and Application Engineering
Online patent databases are powerful resources for tech mining and social network analysis and, especially, identifying rising technology stars in co-inventor networks. However, it’s difficult to detect them to meet the different needs coming from various demand sides. In this paper, we present an unsupervised solution for identifying rising stars in technological fields by mining patent information. The solution integrates three distinct aspects including technology performance, sociability and innovation caliber to present the profile of inventor, meantime, we design a series of features to reflect multifaceted ‘potential’ of an inventor. All features in the profile can get weights through the Entropy weight method, furthermore, these weights can ultimately act as the instruction for detecting different types of rising technology stars. VantagePoint used in data preprocessing. A K-Means algorithm using clustering validity metrics automatically groups the inventors into clusters according to the strength of each inventor’s profile. In addition, using the nth percentile analysis of each cluster, this paper can infer which cluster with the most potential to become which type of rising technology stars. Through an empirical analysis, we demonstrate various types of rising technology stars: (1) tech-oriented RT Stars: growth of output and impact in recent years, especially in the recent 2 years; active productivity and impact over the last 5 years; (2) social-oriented RT Stars: own an extended co-inventor network and greater potential stemming from those collaborations; (3) innovation-oriented RT Stars: Various technical fields with strong innovation capabilities. (4) All-round RT Stars: show prominent potential in at least two aspects in terms of technical performance, sociability and innovation caliber. VantagePoint used in data preprocessing.
Author(s): Lin Zhu, Donghua Zhu, Xuefeng Wang,Scott W. Cunningham, Zhinan Wang
Organization(s): Beijing Institute of Technology, Delft University of Technology
Detecting promising technology groups for recombination holds the promise of great value for R&D managers and technology policymakers, especially if the technologies in question can be detected before they have been combined. However, predicting the future is always easier said than done. In this regard, Arthur’s theory (The nature of technology: what it is and how it evolves, Free Press, New York, 2009) on the nature of technologies and how science evolves, coupled with Kuhn’s theory of scientific revolutions (Kuhn in The structure of scientific revolutions, 1st edn, University of Chicago Press, Chicago, p 3, 1962), may serve as the basis of a shrewd methodological framework for forecasting recombinative innovation. These theories help us to set out quantifiable criteria and decomposable steps to identify research patterns at each stage of a scientific revolution. The first step in the framework is to construct a conceptual model of the target technology domain, which helps to refine a reasonable search strategy. With the model built, the landscape of a field—its communities, its technologies, and their interactions—is fleshed out through community detection and network analysis based on a set of quantifiable criteria. The aim is to map normal patterns of research in the domain under study so as to highlight which technologies might contribute to a structural deepening of technological recombinations. Probability analysis helps to detect and group candidate technologies for possible recombination and further manual analysis by experts. To demonstrate how the framework works in practice, we conducted an empirical study on AI research in China. We explored the development potential of recombinative technologies by zooming in on the top patent assignees in the field and their innovations. In conjunction with expert analysis, the results reveal the cooperative and competitive relationships among these technology holders and opportunities for future innovation through technological recombinations.
Author(s): Xiao Zhou, Lu Huang, Yi Zhang, Miaomiao Yu
Organization(s): Xidian University, Beijing Institute of Technology
Lab-on-chip are miniaturized devices capable of performing a variety of chemical, biochemical or biological analyzes of small volumes of fluids into a single chip. This is an emerging technology that holds potential to deliver more reliable and faster results at a lower cost than traditional laboratory methods. The aim of this paper is to give an overview of the products and processes related to lab-on-a-chip based on patent documents. We use patents data from Thomson Reuters Derwent Innovations Index and combine bibliometrics and social network analysis techniques. We found 2984 patents related to lab-on-a-chip technology, of which only 221 claims for a new lab-on-a-chip device. Considering the total of patents, our results show a significant increase in patenting from 2000 to 2008. As of 2006, the interest in patenting in several countries has risen. USA and Japan are the two most frequent countries developing related technologies, and the USA and the European Patent Office are the top target of patenting by non-residents. Overall, one can see a wide dispersion of organizations involved in researching and developing this technology. Technological developments are most frequently associated with the areas of physics, performing operations and chemistry. Most of the documents are aimed to protect inventions related to instruments for measuring and testing, and processes or apparatus for separation or mixing. By providing a lab-on-a-chip patent landscape worldwide, our findings can be used to support R&D decisions and foster new partnerships between organizations willing to develop the capabilities needed to enter this market.
Author(s): Flávia Maria Lins Mendes, Kamaiaji Castor, Roseli Monteiro, Fabio Batista Mota, Leonardo Fernandes Moutinho Rocha
Organization(s): Centro de Estudos Estratégicos, Fundação Oswaldo Cruz (CEE/Fiocruz)
Source: World Patent Information