• Resources Recycling
• /
• v.22 no.1
• /
• pp.72-79
• /
• 2013

There is increasing interest to the development of environmental friendly products related global environment and health issue and it is very important technology for recycling contained hazardous substance that occur due to oxidation during used oils and fats of vegetable and animal to eco-friendly products. In this study, papers and patents for recycling technologies of used fat and vegetable oil as monomers were analyzed. The range of search was limited in the open patents of USA (US), European Union (EP), Japan (JP), Korea (KR) and SCI journals from 1976 to 2012. Patents and journals were collected using key-words searching and filtered by filtering criteria. The trends of the patents and journals were analyzed by the years, countries, companies, and technologies. Such pretreatment purification, polymerization for monomer, and polymer manufacturing technology were ahead of the United States.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.46 no.4
• /
• pp.15-31
• /
• 2023

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

• Proceedings of the Korea Contents Association Conference
• /
• 2014.06a
• /
• pp.219-220
• /
• 2014

• Journal of the Korean Data and Information Science Society
• /
• v.27 no.5
• /
• pp.1273-1284
• /
• 2016

In this paper, we analyzed the patents on machine learning using keyword network analysis and clique analysis. To construct a keyword network, important keywords were extracted based on the TF-IDF weight and their association, and network structure analysis and clique analysis was performed. Density and clustering coefficient of the patent keyword network are low, which shows that patent keywords on machine learning are weakly connected with each other. It is because the important patents on machine learning are mainly registered in the application system of machine learning rather thant machine learning techniques. Also, our results of clique analysis showed that the keywords found by cliques in 2005 patents are the subjects such as newsmaker verification, product forecasting, virus detection, biomarkers, and workflow management, while those in 2015 patents contain the subjects such as digital imaging, payment card, calling system, mammogram system, price prediction, etc. The clique analysis can be used not only for identifying specialized subjects, but also for search keywords in patent search systems.

• Asian Journal of Innovation and Policy
• /
• v.4 no.3
• /
• pp.307-327
• /
• 2015

This study attempts to develop a methodology that analyzes patent applications to identify future skills, in particular in the sector of information security, recently into the spotlight. Matching skill elements from the International Patent Classification (IPC) with skill units from job analysis, the study tries to track trends in the skills needs based on IPC time-pattern. It then verifies the validity of the outlook for future skills needs by addressing the situation through the use of patents. The research assesses the usability of patent information for this type of analysis. While this study is limited to the information security sector by using Korean patent information, it can be expanded in the future to other areas and patents in the United States and Europe.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2020.11a
• /
• pp.67-68
• /
• 2020

Real-time information on the construction project required by the owner make the project's transparency and overall productivity will be improved. This study analyzes domestic and foreign patents for construction project management to identify trends in technology development, construct cloud-based construction project management system solution UI, and proposes functions and services for each module. Trend research is conducted through patent search, and the analysis is divided into quantitative analysis which means quantitative statistics and qualitative analysis which means the technical contents of each patent. The construction project management system solution is based on smart devices at small and medium-sized sites, allowing both the owner and the construction personnel to share information.

• ETRI Journal
• /
• v.38 no.2
• /
• pp.405-415
• /
• 2016

This research proposes the use of a patent analysis methodology that can suggest promising technology in the ICT sector at the micro-level. This approach identifies core patents from the technology field, groups them as research frontiers (RFs), and develops a visualized network based on the citing relationships to monitor the relationship among RFs. In addition, it calculates a "promising index" based on the growth potential, impact, and marketability of patents to ultimately derive promising RFs. To illustrate the proposed approach, this research presents analysis results for a chosen area, which is the user interface and user experience (UI/UX) technology field. By proposing promising technological fields at the micro-level, the proposed methodology will serve as a useful decision-making support tool in selecting R&D projects, technology planning, and determining technology policy direction.

• Journal of Digital Convergence
• /
• v.18 no.3
• /
• pp.1-12
• /
• 2020

The purpose of this study is to explore the trend of blockchain technology through analysis of patents and news articles using text mining, and to suggest the blockchain policy agenda by grasping social interests. For this purpose, 327 blockchain-related patent abstracts in Korea and 5,941 full-text online news articles were collected and preprocessed. 12 patent topics and 19 news topics were extracted with latent dirichlet allocation topic modeling. Analysis of patents showed that topics related to authentication and transaction accounted were largely predominant. Analysis of news articles showed that social interests are mainly concerned with cryptocurrency. Policy agendas were then derived for blockchain development. This study demonstrates the efficient and objective use of an automated technique for the analysis of large text documents. Additionally, specific policy agendas are proposed in this study which can inform future policy-making processes.

• The Journal of the Korea Contents Association
• /
• v.18 no.10
• /
• pp.443-452
• /
• 2018

With the explosively increasing intellectual property rights, securing technological competitiveness of companies is more and more important. In particular, since patents include core technologies and element technologies, patent analysis researches are actively conducted to measure the technological value of companies. Various patent analysis studies have been conducted by the International Patent Classification(IPC), which does not include the latest technical classification, and the technical classification accuracy is low. In order to overcome this problem, the Cooperative Patent Classification(CPC), which includes the latest technology classification and detailed technical classification, has been developed. In this paper, we propose a model to analyze the classification of the technologies included in the patent by using the detailed classification system of CPC. It is possible to analyze the inventor's patents in consideration of the relation, importance, and efficiency between the detailed classification schemes of the CPCs to extract the core technology fields and to analyze the details more accurately than the existing IPC-based methods. Also, we perform the comparative evaluation with the existing IPC based patent analysis method and confirm that the proposed model shows better performance in analyzing the inventor's core technology classification.

• Clean Technology
• /
• v.18 no.3
• /
• pp.307-311
• /
• 2012

Patents is a strong asset. Samsung and Apple's patent lawsuit is a prime example. So many countries reinforce the intellectual property and they lay the emphasis on the patent. Utilizing the patent information efficiently is basic to the patent analysis. Patent information will provide for new science and technology information sources, international code is classified according to the international patent system IPC, being easily accessible. In this paper, analysis of foreign and domestic patents for zeolite technologies analysis using IPC. The current of technology development in such countries as Korea, USA, Japan, China and EU was analyzed by classifying the patents for 1992 through 2011 according to registration country, assignee, calendar year and technology area.