• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.2
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• pp.99-107
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• 2024

The recent digital transformation in many industries has led to an explosion of data, which has exponentially increased the amount of data that companies need to generate and process. As a result, enterprises are leveraging ERP systems to manage and analyze large amounts of data in real time. However, due to cost and time issues in processing large amounts of data in existing ERP systems, it is essential to apply data archiving technology that can compress and store data in real time in existing systems. Therefore, this paper aims to identify the trends of the target technology by utilizing patent data on ERP-based real-time data archiving technology, analyze the core patents, and create new core patents based on them.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.341-346
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• 2011

A vacant technology forecasting is an important issue in management of technology. The forecast of vacant technology leads to the growth of nation and company. So, we need the results of technology developments until now to predict the vacant technology. Patent is an objective thing of the results in research and development of technology. We study a predictive method for forecasting the vacant technology quantitatively using patent data in this paper. We propose an ensemble model that is to vote some clustering criteria because we can't guarantee a model is optimal. Therefore, an objective and accurate forecasting model of vacant technology is researched in our paper. This model combines statistical analysis methods with machine learning algorithms. To verify our performance evaluation objectively, we make experiments using patent documents of diverse technology fields.

• Journal of Digital Convergence
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• v.12 no.9
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• pp.169-175
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• 2014

The ICT (information and communication technology) paradigm shift, including the burgeoning use of mobile, SNS, and smart devices, has resulted in an explosion of data along with lifestyle changes. We have thus arrived at the age of big data. In the meantime, a number of difficulties have arisen in terms of cost or on the technical side with respect to the use of large quantities of data. However, big data has begun to receive attention with the advent of efficient big data technologies such as Hadoop. In this paper, we discuss the patent analysis of big data platform technology research and development in major countries. Especially, we analyzed 2,568 patent applications and registered patents in four countries on December 2010.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.5
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• pp.955-960
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• 2012

In this paper, we analysis a competition to organize knowledge map as initial prepare stage based on intellectual property. We also propose the method that can be used to constitute knowledge map related in area to use basic data. In order to extract analysis data, we choose LED as an analysis technology. We provide the result of total analysis for LED application area through analysis of patent level after we extract recent patent ratio, activity index, patent family size, cites per patent as center of patent data.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.11a
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• pp.763-777
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• 2017

기술집약적 산업의 급격한 기술혁신 속도 및 환경변화에 따른 기술수명 주기의 단축, 기술간 경쟁을 통한 시장지배력의 우위를 선점하기 위해 기술융합을 통한 연구전략 수립은 중요한 이슈가 되고 있다. 최근 4차 산업혁명 기반의 반도체산업이 이러한 예이며, 이와 같은 기술집약적 산업의 기술융합이 매우 중요해짐에 따라, 관련 전략수립을 위한 다양한 방법이 시도되고 있다. 본 논문에서는 데이터 기반의 논문 특허 분석을 통해 반도체산업의 플라즈마 기술이슈의 기술융합 동향 및 특허 동향 분석과 이를 통한 특허 전략 수립 사례를 제시하고자 한다.

• Proceedings of the Technology Innovation Conference
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• 2003.02a
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• pp.121-135
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• 2003

기술 패러다임의 변화는 전체 산업구조를 변화시킬 뿐 아니라 새로운 산업 분야를 만들어내고 현존하는 산업분야 내의 기술을 변화시킨다. 기술혁신의 산업별 유형에 관한 Paviit의 연구는 이러한 산업분야 별 기술적 특성의 다양성, 즉 기술 패러다임 변화에 토대를 두고 있으며 그의 산업분류는 많은 후행 연구에서 인용되어 왔다. 그럼에도 불구하고 Paviit의 연구는 분석이 특정 시기에 국한되고, 정량적 분석이나 시간의 흐름을 고려한 동적 분석이 부족하며 일부 산업분야의 데이터가 미흡하다는 점 등, 데이터 분석과 관련된 몇 가지 한계점을 가지고 있다. 따라서 본 논문에서는 Paviit 연구의 한계점을 극복하고자 1975년과 1999년 사이에 미국특허청(USPTO)에 등록된 특허에 대한 자료 및 특허인용에 대한 자료를 이용하여 실험적인 분석을 실시하였다. 산업구조의 변화를 고려하여 Pavitt이 제시한 4개의 산업 유형은 1)공급자 지배형(Supplier dominated), 2)규모 집약형(Scale intensive), 3)전문 공급자형 (Specialized suppliers), 4)화학 기반형(Chemical science based), 5)생명과학 기반형(Bio-science based), 6)정보과학 기반형 (Information science based)의 6개로 확장되었다. 이와 같이 도출된 각 산업 유형 별로 A)특허 네트워크(Patent Network), B)기술 궤적 (Technology Trajectory) 두 가지 측면에서 분석을 실시하였다. 우선 특허 네트워크 분석은 기술발달 과정에서의 지식 흐름을 연구하기 위한 분석으로, 산업 내 분석으로는 각 산업에 속한 특허들의 관계의 측면에서 긴밀성을 나타내는 네트워크 밀도와 기술 지식의 집중 정도를 나타내는 네트워크 중심도를 산출하였고 산업간 분석으로는 산업간 지식 흐름의 양상을 살펴보았다. 또한, 기술 궤적 분석에서는 각 산업별 기술의 특성을 분석하는 것으로, 특정 기술 지식의 활용 기간을 통해 기술 주기를 도출하고, 산업 내 평균 권리 청구 항목 수를 이용하여 각 산업의 기술 범위를 비교하였다. 각각의 동적 분석을 통해 시간에 따른 변화 양상이 관찰하였고, ANOVA 분석을 이용하여 통계적 유의성을 검증하였다. 본 연구는 현재의 기술 패러다임 내에서 Pavitt이 제시한 산업 분류의 근거를 보충 설명하였고 특허 정보를 이용하여 기술혁신의 산업별 유형에 대한 폭넓은 분석방법을 제시하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.66-67
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• 2014

This study is to compare and analyze the technology competitiveness of Big Data sector through patent analysis. According to results of the analysis, the United States is the most active country on the patent activities and its applied and registered patents have multiplied in recent times. However, both CPP(Cited Per Patent) and PII(Patent Impact Index) of the US would have declined, indicating that the growth of technology in the US seems to be biased to quantitative growth of technologies. Korea has been relatively active patent activities with Japan, China and Canada, whereas it has tended to be biased to quantitative growth with the US; Therefore, Korea government needs to concentrate efforts to retain the high quality technologies.

• Journal of Labour Economics
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• v.41 no.3
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• pp.161-186
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• 2018

Albeit numerous endeavors in matching names and surveying inventors, inventor-level studies of patent data have been scarce because unique inventors can not be identified across patents. Using the Korean patent data with inventor IDs, birth year, and gender available, we construct unique inventor-level panel data. As the first undertaking with our data, we investigate the age profile of patent productivity among inventors. We find an inverted U-shaped profile with the peak at age 31. We also find an increasing productivity for younger cohorts of inventors. These findings are robust after we control for the calendar year effects and the quality of patents.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.8
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• pp.1049-1054
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• 2018

Keyword searching used in the past as a method of finding similar patents, and automated classification by machine learning is using in recently. Keyword searching is a method of analyzing data that is formalized through data refinement. While the accuracy for short text is high, long one consisted of several words like as document that is not able to analyze the meaning contained in sentences. In semantic analysis level, the method of automatic classification is used to classify sentences composed of several words by unstructured data analysis. There was an attempt to find similar documents by combining the two methods. However, it have a problem in the algorithm w the methods of analysis are different ways to use simultaneous unstructured data and regular data. In this paper, we study the method of extracting keywords implied in the document and using the LDA(Latent Semantic Analysis) method to classify documents efficiently without human intervention and finding similar patents.

• Patent21
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• s.62
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• pp.8-15
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• 2005

본 보고서는 일본의 경제연구소(RIETI)에서 발간한 보고서로서 특허인용문에 쓰이는 일반적인 과학저널의 데이터를 대상으로 분석을 실시한 것이다.