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

• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.77-88
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• 2017

Recently, with the advent of knowledge based society where information and knowledge make values, patents which are the representative form of intellectual property have become important, and the number of the patents follows growing trends. Thus, it needs to classify the patents depending on the technological topic of the invention appropriately in order to use a vast amount of the patent information effectively. IPC (International Patent Classification) is widely used for this situation. Researches about IPC automatic classification have been studied using data mining and machine learning algorithms to improve current IPC classification task which categorizes patent documents by hand. However, most of the previous researches have focused on applying various existing machine learning methods to the patent documents rather than considering on the characteristics of the data or the structure of patent documents. In this paper, therefore, we propose to use two structural fields, technical field and background, considered as having impacts on the patent classification, where the two field are selected by applying of the characteristics of patent documents and the role of the structural fields. We also construct multi-label classification model to reflect what a patent document could have multiple IPCs. Furthermore, we propose a method to classify patent documents at the IPC subclass level comprised of 630 categories so that we investigate the possibility of applying the IPC multi-label classification model into the real field. The effect of structural fields of patent documents are examined using 564,793 registered patents in Korea, and 87.2% precision is obtained in the case of using title, abstract, claims, technical field and background. From this sequence, we verify that the technical field and background have an important role in improving the precision of IPC multi-label classification in IPC subclass level.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1499-1505
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• 2015

This study is about the patent information analysis of relevant companies and technologies based on International Patent Classification (IPC) code. 902 patent applications in the field of electronic commerce(G06Q) by NAVER, the biggest internet company in Korea, are the subjects of this study. First, we investigated the number of applications and registrations per IPC code so that we could analyze the core technology areas and the status of patent application. In addition, we examined the convergence of technologies by investigating interconnections between main and sub categories of IPC codes. Lastly, we looked into the changes in patent technologies by investigating the status of application per IPC code in accordance with year. By analyzing the IPC code based patent information used in this study, we could further expect the trends of companies and technologies.

• Korean Journal of Oriental Medicine
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• v.11 no.2
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• pp.67-96
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• 2005

This Study focused on IPC (International Patent Classification) for TKM (Traditional Korea Medicine) Paper. The results processed for 9,000 TKM paper by using 8th in IPC Classification. The name of Herbal Medicine assigned to IPC Classification, we assigned to two part for main-Classification(A61K) and sub-Classification (A61P). The results obtained about 77% for A61K and about 96% for A61K36 among them. And also analysed about 23% for sub-Classification(A61P) additionally. Main-Classification is distributed A61K > A61H37 > A61B5 > A61N > A61M1. Detailed Main-Classification for A61K is distributed A61K36 > A61K35 > A61K33 among Main-Classification. TKM Paper mainly analysed A61K36 and A61H37 in Main-Classification. According to the results. 'The Korean Journal of Herbology' has high-valued for Utilization as a Non Patent Document. we should constructed Database system for protection of intellectual property rights. And after We will registered minimum documentation of PCT.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.190-195
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• 2016

A technology is continuously developed in a rapidly changing global market. A company requires an appropriate R&D strategy for adapting to this environment. That is, the technologies owned by the company needs to be thoroughly analyzed to improve its competitiveness. Alternatively, technology classification using IPC codes is carried out recently in an objective and quantitative way. International Patent Classification, IPC is an internationally specified classification system, so it is helpful to conduct an objective and quantitative patent analysis of technology. In this study, all of the patents owned by company C are investigated and a matrix representing IPC codes of each patent is created. Then, a structured association map of the patents is made through association rules mining based on Confidence. The association map can be used to inspect the current situation of a company about patents. It also allows highly associated technologies to be clustered. Using the association map, this study analyzes the technologies of company C and how it changes with time. The strategy for future technologies is established based on the result.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.2
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• pp.294-302
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• 2009

In this paper, the trend of technology and the business strategy on 'Hearing Aids' are investigated for the industry promotion of medical devices based on IT engineering from the 316 patents of 'Hearing Aids' registered in Korean Intellectual Property Office(KIPO). The classification of technology on 'Hearing Aids' is performed according to the IPC(International Patent Classification) code to and the core technology of 'Hearing Aids' As the results of classification of IPC code, the number of patents with IPC code 'H04R', 'H04B', 'H01M', and 'A61F' are 160, 46, 40, and 19 respectively. We found that the Digital technology and the Medical Transplants technology are come to the front of 'Hearing Aids' and the foreign 'Hearing Aids' companies are filed an application with the Korean Intellectual Property Office(KIPO) before their business.

• Annual Conference on Human and Language Technology
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• 2019.10a
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• pp.347-350
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• 2019

인공지능 관련 기술의 발달로 다양한 분야에서 인공지능 활용에 대한 관심이 고조되고 있으며 전문영역에서도 기계학습 기법을 활용한 연구들이 활발하게 이루어지고 있다. 특허청에서는 분야별 전문지식을 가진 분류담당자가 출원되는 모든 특허에 국제특허분류코드(이하 IPC) 부여 작업을 수행하고 있다. IPC 분류와 같은 전문적인 업무영역에서 딥러닝을 활용한 자동 IPC 분류 서비스를 제공하기 위해서는 기계학습을 이용하는 분류 모델에 분야별 전문지식을 직관적으로 반영하는 것이 필요하다. 이를 위해 본 연구에서는 딥러닝 기반의 IPC 분류 모델과 전문지식이 반영된 분류별 어휘사전을 활용한 규칙기반 분류 모델을 병행하여 특허문서의 IPC분류를 자동으로 추천하는 방법을 제안한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.306-311
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• 2015

This study aims at analyzing the convergence of Internet-of-Things and wearables technologies using cooperative patent classification(CPC). CPC, introduced to an increasing number of technological fields of Korean patents, is expected to be widely used in Patent Informatics because the classification codes in CPC are more specific than those of IPC, which reflect the characteristics of technologies in detail with accuracy. CPC has seldom been used up to date and most of the previous researches on technological convergence used IPC. As a pre-analysis step for analyzing the trend of technological convergence of IoT and wearables, CPC and IPC codes assigned to each patent were compared. By applying association rule mining to the analysis of CPC codes, we identified the technological fields where convergence frequently takes place and examined the trend of technological convergence over time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1642-1648
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• 2021

We analyzes representative technologies of IoT patents and reflects these results in the curriculum of IoT. In order to identify the representative technologies, the IPC codes of the patents were analyzed. Among the main category IPC codes, the most used IPC codes were H04L in Single IPC Patent with 974 cases(32.0%) and G06Q in Multiple IPC Patent with 710 cases(29.2%). As a result of classifying the IPC code into the WIPO technology classification system, the most emphasized technologies are Digital Communication, accounting for about 60.5% in the Single IPC Patent and IT Methods for Management(710 cases, 29.2%) in Multiple IPC Patent. The main points to be considered when organizing the curriculum of IoT are: ∇Emphasis on Digital Communication, ∇Expansion of Education related to IT Methods for Management(Including entrepreneurship and patent application), and ∇Consideration of subjects related to the Convergence of IoT. This research can contribute to the curriculum design of new industrial technologies such as AI and Fintech.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.930-932
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• 2015

This study is the basic research about the patent information analysis to predict the technology trend based on the IPC(International Patent Classification) code. We investigated the patents in the field of Business Method(G06Q) since 2011. Consequently the most frequently IPC code in G06Q are as follows. G06Q 50/10(1,652), G06Q 30/02(816), G06Q 50/30(735), G06Q 40/02(713), G06Q 50/22(530), and G06Q 30/06(489).