• Journal of Korean Society for Quality Management
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• v.48 no.1
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• pp.227-239
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• 2020

Purpose: The purpose of this study is to introduce the improving attorney system. It was confirmed by document writing that the staff in the field in Korea had the most difficulty in the Quality circle activities. The reform improving attorney is a quality expert at the Quality Secretariat and assists them in their documentation. Methods: Just as a patent attorney helps to get a patent, an improving attorney system helps document the improvement results of the field Quality circle and even standardizes the company. The process of introducing an improving attorney includes the declaration of an improving attorney are 11 levels of work. Results: An improving attorney was conducted in 600 organizations for 18 months. As a result of the comparison of the number of cases before and after the introduction of the improving attorney, the number of solution problem was lowered to 9 before 2016 and 8 in 2017, but after the introduction, it increased exponentially to 181 in 2018 and 162 in August 2019. In 2016 and 2017, only one standard was registered, but 64 standards were registered in 2018 and 71 in 2019. Conclusion: In this case, the improving attorney system was found to be helpful in activating the Quality circle. It is expected to revitalize Korea's Quality circle by spreading the improving attorney system to many companies.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.277-280
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• 2019

본 논문에서는 화학분야 특허 문서에 존재하는 도표(TABLE) 데이터를 인공지능 기술을 활용하여 자동으로 추출하고 정형화된 형태로 가공하는 방법을 제안한다. 특허 문서에서 도표 데이터는 실시예에서 실험결과나 비교결과를 간결하고 가시적으로 표현하기 위하여 주로 사용되나, 셀의 속성을 정의하는 헤더부분과 수치가 표현되는 값 부분의 경계가 모호하여 구조화하는데 어려움이 있다. 본 논문에서 제안하는 방법은 소량의 학습데이터를 구축하고 기계학습을 통해 도표에 존재하는 셀의 속성을 예측하고, 예측된 속성을 토대로 조성과 물성 정보를 자동으로 구분하여 추출하는 방법을 제시한다. 제시된 방법을 활용하여 화학 분야 조성물 특허의 도표데이터에 시뮬레이션 결과 각 항목별 98.17%의 속성 예측 정확도를 나타내었으며 기존 규칙기반 연구보다 작업난이도, 예측정확도에서 우수한 성과를 보인다.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.4
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• pp.145-152
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• 2020

MRC (Machine reading comprehension) is the AI NLP task that predict the answer for user's query by understanding of the relevant document and which can be used in automated consult services such as chatbots. Recently, the BERT (Pre-training of Deep Bidirectional Transformers for Language Understanding) model, which shows high performance in various fields of natural language processing, have two phases. First phase is Pre-training the big data of each domain. And second phase is fine-tuning the model for solving each NLP tasks as a prediction. In this paper, we have made the Patent MRC dataset and shown that how to build the patent consultation training data for MRC task. And we propose the method to improve the performance of the MRC task using the Pre-trained Patent-BERT model by the patent consultation corpus and the language processing algorithm suitable for the machine learning of the patent counseling data. As a result of experiment, we show that the performance of the method proposed in this paper is improved to answer the patent counseling query.

• Journal of The Korean Digital Architecture Interior Association
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• v.12 no.1
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• pp.81-88
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• 2012

According to the survey results of the Ministry of Land, Transport and Maritime Affairs in the end of December 2011, the residential buildings was reported as 67.3% of 4,529,464 buildings. Reflected in the national energy policy, the residential building is expected that greater energy savings. To have realized the Passive House Project used the Autoclaved Lightweight Concrete(ALC) material on exterior wall, we take advantage of a very large energy savings. Therefore, this study investigate the patent documents of three major companies, SUMITOMO, CLION, ASAHI KASEI, in Japan. and analyze technical flow and benchmarking patent. As a result, the Sliding method or the Rocking method of ALC panels how to install is to be superior to high-performance drift and safety by a earthquake. And the embedded anchor in panel needs to improve the shape and the strength of bearing. Thus installation technology of the ALC exterior wall investigated in japanese patent documents is expected to the fastening units and anchors.

• The Journal of Industrial Distribution & Business
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• v.6 no.3
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• pp.27-33
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• 2015

Purpose - This paper's aim is to analyze the technological information in patent databanks as a strategy in prospecting for new technologies. Research design, data, and methodology - We detail the major free electronic database sources for patent information, the patent documents, the patent document structures, INID codes (Internationally Agreed Numbers for the Identification of Data), indexation, references, and classification notions. Additionally, we review and analyze information on the activities of the Center of Dissemination Documentation and Technological Information (CEDIN) from the National Institute of Intellectual Property (INPI) of Brazil for the period 2000 to 2011. Results - The research shows that the technological information contained in the patents could provide a wide range of functionality within companies and universities. Conclusions - In recent years, (CEDIN), a specialist in intellectual property, has been serving internal and external users by providing guidance on the basis of patents and other literature, but the number of users served is still small. In order to familiarize more potential users of such technological information, task forces should be created among INPI, universities, and companies.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.392-397
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• 2015

Society has been developed through analogue, digital, and smart era. Every technology is going through consistent changes and rapid developments. In this competitive society, R&D strategy establishment is significantly useful and helpful for improving technology competitiveness. A patent document includes technical and legal rights information such as title, abstract, description, claim, and patent classification code. From the patent document, a lot of people can understand and collect legal and technical information. This unique feature of patent can be quantitatively applied for technology analysis. This research paper proposes a methodology for extracting core technology and patents based on quantitative methods. Statistical analysis and social network analysis are applied to IPC codes in order to extract core technologies with active R&D and high centralities. Then, core patents are also extracted by analyzing citation and family information.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.1-15
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• 2022

This study analyzes the relationship of citations appearing in the patent data to understand knowledge transfers and impacts between patent documents in the field of pharmaceutical research. Patent data were collected from a website, Google Patents. The top 25 assignees were selected by searching for patent documents related to pharmaceutical research. We identify the citation relationships between assignees, then calculate and compare the values of h-index and derived indicators by using the number of citations and rank for each document of each assignee. As a result, in the case of pharmaceutical research, the assignee, such as 'Pfizer, MIT, and Abbott' shows a high impact. Among the five bibliometric indicators, the g-index and hS-index show similar results, and the indicators are the most related to the rankings of Total Citation Frequency, Cites per Patents, and Maximum Citation Frequency. In addition, it is highly related to the five indicators in the order of Total Citation Frequency, Cites per Patents, and Maximum Citation Frequency. In some cases, it is difficult to make an accurate comparison with Cites per Patents alone, which is previously known to indicate the technological influence of patent assignees.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.139-149
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• 2013

As the importance of technology forecasting while countries and companies manage the R&D project is growing bigger, the methodology of technology forecasting has been diversified. One of the forecasting method is patent analysis. This research proposes quick forecasting process of emerging technology based on keyword approach using text mining. The forecasting process is following: First, the term-document matrix is extracted from patent documents by using text mining. Second, emerging technology keyword are extracted by analyzing the importance of word from utilizing mean values and standard deviation values of the term and the emerging trend of word discovered from time series information of the term. Next, association between terms is measured by using cosine similarity. finally, the keyword of emerging technology is selected in consequence of the synthesized result and we forecast the emerging technology according to the results. The technology forecasting process described in this paper can be applied to developing computerized technology forecasting system integrated with various results of other patent analysis for decision maker of company and country.

• 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.