• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.227-237
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• 2022

With the growing interest in convergence, there have been various attempts to measure convergence, but the definition of convergence is ambiguous and consensus on appropriate indicators has not been reached, so measurement of convergence is still at a rudimentary stage. In this study, using the KSIC-IPC linkage table developed by the Korean Intellectual Property Office to analyze the correlation and impact of patents, industry, economy, and population, we propose a new evaluation model that can evaluate industry convergence from patent data. In addition, it was verified whether the industry convergence derived from this properly reflects the corporate convergence characteristics. As a result of classifying the convergence of 39,740 patents owned by global major automobile companies, and evaluating the degree of convergence of each company, it was confirmed that the industry convergence derived using the KSIC-IPC linkage table better reflects the corporate convergence characteristics than the technology convergence classified by IPC co-classification. Therefore, the industry convergence data of automotive sector derived from the new industry convergence evaluation model using the KSIC-IPC linkage table is expected to be widely used for future convergence research.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.21-33
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• 2022

Purpose: As most defense technologies are classified as confidential, the corresponding International Patent Classifications (IPCs) require special attention. Consequently, the list of defense-related IPCs has been managed by the government. This paper aims to evaluate the defense-related IPCs and propose a methodology to revalidate and improve the IPC classification scheme. Methods: The patents in military technology and their corresponding IPCs during 2009~2020 were utilized in this paper. Prior to the analysis, patents are divided into private and public sectors. Social network analysis was used to analyze the convergence structure and central defense technology, and association rule mining analysis was used to analyze the convergence pattern. Results: While the public sector was highly cohesive, the private sector was characterized by easy convergence between technologies. In addition, narrow convergence was observed in the public sector, and wide convergence was observed in the private sector. As a result of analyzing the core technologies of defense technology, defense-related IPC candidates were identified. Conclusion: This paper presents a comprehensive perspective on the structure of convergence of defense technology and the pattern of convergence. It is also significant because it proposed a method for revising defense-related IPCs. The results of this study are expected to be used as guidelines for preparing amendments to the government's defense-related IPC.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.266-272
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• 2016

In this study, we analysed the technology convergence of Internet of Things(IoT) by International Patent Classification(IPC) code analysis. 163 patent applications in Korea are the subjects of this study. We confirmed that the most representative IPC code combinations between Main and Sub categories are G06Q 50/24-G06Q 50/22(6 cases), H04L 29/02-H04L 12/28(4 cases), G06F 15/16-G06F 3/048(3 cases), G06F 15/16-G06F 9/44(3 cases), and G06Q 50/22-G06Q 50/24(3 cases). The field of Health Care business have been prepared 9 patent applications by technology convergence between 'Health Care(G06Q 50/22)' and 'Patient Record Management(G06Q 50/24)'. Finally we also concluded that the core IPC code are G06F 15/16, G06Q 50/22, G06Q 50/24, and H04L 12/28 by the technology convergence interconnections analysis of IoT patent applications.

• Genomics & Informatics
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• v.10 no.4
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• pp.271-274
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• 2012

Whereas a vast amount of new information on bioinformatics is made available to the public through patents, only a small set of patents are cited in academic papers. A detailed analysis of registered bioinformatics patents, using the existing patent search system, can provide valuable information links between science and technology. However, it is extremely difficult to select keywords to capture bioinformatics patents, reflecting the convergence of several underlying technologies. No single word or even several words are sufficient to identify such patents. The analysis of patent subclasses can provide valuable information. In this paper, I did a preliminary study of the current status of bioinformatics patents and their International Patent Classification (IPC) groups registered in the Korea Intellectual Property Rights Information Service (KIPRIS) database.

• Journal of the Ergonomics Society of Korea
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• v.34 no.5
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• pp.501-517
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• 2015

Objective: The aim of this study was to investigate the technology trend on developing helmets based on the analysis of Korean, US, European and PCT patents. Background: The usage of the personal protective equipment such as the safety helmet would be essential for preventing injuries and reducing the severity of injuries depending on the type of activity and the exposed environment. Method: Database of WIPSON was used for searching the patents. The objects were the Korean, US, European and PCT patents registered or opened from January 2011 to December 2014. The keyword to investigate was helmet, and International Patent Classification (IPC) was used for investigating the technology trend of the patents. Results: The cases of US patents annually increased, but the cases of European patents decreased. US patents belonged to all sections but Korean and European patents and PCT patents did not. The largest number of IPC, to which four areas' patents belonged, was 'Headwear' and the second largest one was 'Hygiene'. In the subgroup level, the most common largest subgroups were 'Parts, details or accessories of helmets' and 'Masks, shields, or hoods for welders'. Korean patents had the lowest ratio of single_IPC at 11%, but the ratios of single_IPC for US and European patents were 52%, respectively. 'Human necessities', 'Mechanical engineering', 'Physics', and 'Electricity' were used as a single_IPC, but lower levels of 'Performing operations', 'Chemistry', 'Textiles' and 'Fixed constructions' were used as multi_IPC. Most main applicants had patents which belonged to 'Human necessities'. Conclusion: The cases of US patents annually increased unlike others. The common technologies for creating the helmet were Parts of helmets under Headwear and Shields for welders under Hygiene. Many Korean patents tended to be categorized as multi_IPC, different from others. Application: To know the technological characteristic of patents would be helpful to initial stage developers.

• Journal of the Korean Society for Library and Information Science
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• v.46 no.4
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• pp.99-117
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• 2012

This paper proposes a method of using national R&D patents' CoIPC networks to identify interdisciplinary trends of technology areas related to Korean national R&D. While previous research analyzed interdisciplinarity of national R&D with simple bibliometric descriptions, this research uses the network-based indexes to analyze its interdisciplinarity from the viewpoints of interdisciplinary "diversity of coupling" and "strength of coupling". In this research, this proposed method was used to form a R&D CoIPC network from the Korean national R&D patents registered from 2007 to 2010. It is expected that the proposed method can be incorporated into a system for a national R&D trend analysis, and used to identify the issues of technology convergence in national R&D and formulate its related research policies.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.367-368
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• 2023

4차 산업혁명으로 다양한 기술과 아이디어가 생겨나고 있고, 이를 보호하기 위한 특허는 그 등록 건수가 매년 증가하는 추세이다. 그러나 현재 특허문서를 분류하는 과정을 수동으로 진행하고 있기에 이를 자동으로 진행할 수 있는 분류기를 생성할 필요를 느꼈고, 본 논문에서는 특허문서를 분류기에 적용할 데이터의 전처리 과정 중 데이터 변환과 통합 과정을 다루었다.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.35-44
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• 1998

This paper describes multiple fault diagnosis method in complex system with hierarchical structure. Complex system is divided into subsystem, item and component. For diagnosing this hierarchical complex system, it is necessary to implement special neural network. We introduced Modular Artificial Neural Network(MANN) for this purpose. MANN consists of four level neural network, first level for symptom classification, second level for item fault diagnosis, third level for component symptom classification, forth level for component fault diagnosis. Each network is multi layer perceptron with 7 inputs, 30 hidden node and 7 outputs trained by backpropagation. UNIX IPC(Inter Process Communication) is used for implementing MANN with multitasking and message transfer between processes in SUN workstation. We tested MANN in reactor system.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.9-16
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• 2018

In this paper, we propose wide range of categorizes Artificial Intelligence technology as Learning, Inference, and Cognitive. Also, it analyzes 758 cases of open patents. For an analysis, target technologies were selected and categorized into specific areas to collect information about the patents. After removing noise, the patent information for each technology such as patent assignees and IPC code, was analyzed to evaluate the maturity of technology, the way ahead for research and development and the trends in core technology. This research presents directions of Artificial intelligence technology research and trend analysis of core Artificial Intelligent technology using quantitative analysis of patent information. Also Artificial intelligence technology requires technological development necessity through close cooperation in diverse fields.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.239-241
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• 2019

지식과 정보의 중요성이 강조되는 지식기반사회에서는 지식재산권의 대표적인 유형인 특허의 중요성이 날로 높아지고 있고, 그 수 또한 급증하고 있다. 특허 문서의 효과적 검색과 이용을 위해서는 새롭게 출원되는 특허 문서의 체계적인 분류 작업이 선행되어야 하고, 따라서 방대한 양의 특허 문서를 자동으로 분류해주는 시스템이 필요하다. 본 연구에서는 Doc2Vec 모델을 이용하여 국내 특허 문서의 특징(feature)을 추출하고, 추출된 특징을 바탕으로 한 특허 문서의 자동 분류 모형을 제안한다. 먼저 국내에 등록된 31,495 건의 특허 문서의 IPC(International Patent Classification)와 요약정보를 바탕으로 Doc2Vec 모델을 구축하였다. 구축된 Doc2Vec 모델을 통하여 훈련데이터의 특징을 추출한 후, 이 특징 벡터를 이용하여 분류기를 학습하였다. 마지막으로 Doc2Vec 모델을 이용하여 실험데이터의 특징 벡터를 추출하고 분류기의 성능을 실험한 결과, 43%의 분류 정확도를 얻었다. 이를 통해, 특허 문서 분류 문제에 Doc2Vec 모델의 사용 가능성을 확인할 수 있었다.