특허정보를 이용한 인공지능 기술 동향 분석

박재용(Jae-Yong Park) 한국컴퓨터정보학회 2018 韓國컴퓨터情報學會論文誌 Vol.23 No.4

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.

인공지능의 기술 혁신 및 확산 패턴 분석: USPTO 특허 데이터를 중심으로

백서인(Seoin Baek),이현진(Hyunjin Lee),김희태(Heetae Kim) 한국콘텐츠학회 2020 한국콘텐츠학회논문지 Vol.20 No.4

인공지능(Artificial Intelligence, AI) 분야는 거의 모든 산업과 결합하여 미래 초연결 및 초지능 시대를 이끌어갈 기술로 주목받고 있다. 우리나라는 미국, 일본, 독일과 함께 인공지능 강국에 손꼽히지만, 인공지능 G2인 미국, 중국에 비해서는 특허 경쟁력이 낮은 것이 사실이다. 본 연구에서는 인공지능 산업의 기술 추이를 유추하고 인공지능 기술의 분야 별 수명주기와 발전 속도를 가늠해보고자 IPC 기술분류코드를 USPTO의 2008년부터 2018년까지 등록된 인공지능 관련특허를 수집하여 1차원 통계분석, 2차원 통계분석, 네트워크 분석을 통해 기술 혁신과 확산 패턴을 분석하였다. 연구결과 현재 인공지능 관련 기술은 디지털 컴퓨팅, 데이터 처리, 음성인식 등 분야에 집중된 것으로 나타났으며, 응용분야의 특허가 증가하고, 전기 통신, 의료, 운수/물류 등에 활발한 융·복합이 일어나고 있는 것을 알 수 있었다. 본 연구를 통하여 분석된 인공지능 산업의 발전추이와 기술동향은 인공지능 기술과 관련한 기업의 전략과 국가의 정책 입안에 활용될 수 있을 것으로 기대한다. The artificial intelligence (AI) is a technology that will lead the future connective and intelligent era by combining with almost all industries in manufacturing and service industry. Although Korea is one of the worlds leading artificial intelligence group with the United States, Japan, and Germany, but its competitiveness in terms of artificial intelligence patent is relatively low compared to others. Therefore, it is necessary to carry out quantitative analysis of artificial intelligence patents in various aspects in order to examine national competitiveness, major industries and future development directions in artificial intelligence technology. In this study, we use the IPC technology classification code to estimate the overall life cycle and the speed of development of the artificial intelligence technology. We collected patents related to artificial intelligence from 2008 to 2018, and analyze patent trends through one-dimensional statistical analysis, two-dimensional statistical analysis and network analysis. We expect that the technological trends of the artificial intelligence industry discovered from this study will be exploited to the strategies of the artificial intelligence technology and the policy making of the government.

특허데이터 기반 한국의 인공지능 경쟁력 분석: 특허지표 및 토픽모델링을 중심으로

이현상,오세환,차오신,신선영,김규리 한국지능정보사회진흥원 2022 정보화정책 Vol.29 No.4

With the development of artificial intelligence technology, competition for artificial intelligence technology patents around the world is intensifying. During the period 2000 ~ 2021, artificial intelligence technology patent applications at the US Patent and Trademark Office have been steadily increasing, and the growth rate has been steeper since the 2010s. As a result of analyzing Korea's artificial intelligence technology competitiveness through patent indices, it is evaluated that patent activity, impact, and marketability are superior in areas such as auditory intelligence and visual intelligence. However, compared to other countries, overall Korea's artificial intelligence technology patents are good in terms of activity and marketability, but somewhat inferior in technological impact. While noise canceling and voice recognition have recently decreased as topics for artificial intelligence, growth is expected in areas such as model learning optimization, smart sensors, and autonomous driving. In the case of Korea, efforts are required as there is a slight lack of patent applications in areas such asf raud detection/security and medical vision learning. 인공지능 기술의 발전과 더불어 세계 각국의 인공지능 기술 특허를 둘러싼 경쟁도 치열해지고 있다. 2000년~2021년 간 미국 특허청의 인공지능 기술 특허출원은 꾸준히 증가하고 있는 가운데 2010년대 들어 보다 가파른 성장세를 기록하고 있다. 특허지표를 통해 한국의 인공지능 기술경쟁력을 분석한 결과, 청각지능, 시각지능 등의 세부 분야에서 특허활동성, 영향력, 시장성 등이 우위에 있는 것으로 평가된다. 그러나, 주요국과 비교하여 한국의 인공지능 기술 특허는 양적 활동성, 시장성 확보 측면에서는 상대적으로 우수하나 기술 파급력은 다소 열위에 있는 것으로 나타난다. 최근 인공지능 기술 토픽으로 노이즈 캔슬링, 음성인식 등은 감소한 반면 모델학습 최적화, 스마트센서, 자율주행 등이 활성화되면서 성장이 기대되고 있다. 한국의 경우 사기탐지/보안, 의료 비전러닝 등의 분야에서 특허출원 성과가 다소 부족하여 분발이 요구된다.

특허 분석을 통한 인공지능 기술경쟁력 변화 과정에 관한 연구 - 주요 5개국을 중심으로 -

황명호,남은영,박세훈,Huang, Minghao,Nam, Eun Young,Park, Se Hoon 한국시스템엔지니어링학회 2022 시스템엔지니어링학술지 Vol.18 No.1

Artificial Intelligence (AI) is to assumed to be one of next generation technology which determine technological competitiveness and strategic advantage of a certain country. By using the patent data, this study aims to have a comparative analysis of the technological competitiveness of evolving artificial intelligence at different stages of development among the five largest intellectual property offices in the world (IP5). For the analysis data, all AI technology patent data from 1956 to 2019 were utilized according to the classification system presented in the "WIPO 2019 Technology Trend: Artificial Intelligence" report published by the World Intellectual Property Organization (WIPO) in 2019. The results shows that China has already surpassed the United States in terms of the number of patent applications in the field of artificial intelligence technology. However, in the domains of the United States, Europe, Japan, and Korea, the technology competitiveness of the United States is far ahead of China. Interestingly, the rate of increase of Korea's technology competitiveness is also very fast, and it has been shown that the technology strength is ahead of China in non-Chinese domains. The significance of this study can be found in the fact that the temporal and spatial change process of technological competitiveness of significant countries in the field of artificial intelligence technology artificial intelligence was viewed as a macro-framework using the technology index (TS) the differences were compared.

인공지능 기술분석을 위한 베이지안 추론

최준혁(Junhyeog Choi),전성해(Sunghae Jun) 한국지능시스템학회 2018 한국지능시스템학회논문지 Vol.28 No.4

인간과 같은 지능을 갖는 컴퓨터를 만드는 인공지능 기술에 대한 눈부신 발전에 의해 사회 각 분야에서 인공지능 기술에 대한 의존도가 점점 커지고 있다. 따라서 인공지능 기술에 대한 정확한 분석에 대한 수요도 지속적으로 증가하고 있다. 따라서 본 논문에서는 인공지능과 관련된 기술분석을 위하여 베이지안 추론 기반의 통계분석 방법에 대하여 연구한다. 현재까지 출원된 인공지능 관련 기술특허를 모두 수집하여 텍스트 마이닝 전처리를 통하여 키워드를 추출하고 이를 이용하여 인공지능 관련 기술분석을 수행한다. 제안방법의 타당성을 확인하기 위하여 인공지능을 위한 2가지 세부기술인 데이터학습과 자연어이해에 대한 키워드를 추출하고 이를 분석하여 실제적용의 가능성을 확인하였다. Due to the remarkable development of artificial intelligence technology that makes computers with intelligence like human beings, artificial intelligence technology is increasingly relied on in each field of society. Therefore, demand for accurate analysis of artificial intelligence technology is continuously increasing. Therefore, in this paper, we study the statistical analysis method based on Bayesian inference for technology analysis related to artificial intelligence. We collect all patents related to artificial intelligence related patents so far, extract keywords through text mining preprocessing, and perform artificial intelligence related technology analysis using them. In order to verify the validity of the proposed method, we considered two sub-technologies which are learning from data and natural language understanding for artificial intelligence, and analyzed the possibility of actual application.

부분최소제곱 회귀분석을 이용한 인공지능 기술분석

최준혁(JunHyeog Choi),전성해(Sunghae Jun) 한국컴퓨터정보학회 2020 韓國컴퓨터情報學會論文誌 Vol.25 No.3

본 논문에서는 부분 최소 제곱(PLS) 회귀 모형을 이용한 인공지능(AI) 기술 분석을 제안한다. AI 기술은 이제 우리 사회의 대부분의 영역에 영향을 미치고 있다. 따라서 이 기술에 대한 정확한 이해가 필요하게 된다. AI 기술을 분석하기 위하여 전 세계 특허 데이터베이스로부터 AI 관련 특허 문서를 수집하고 텍스트 마이닝 기법을 사용하여 수집된 특허 문서에서 AI 기술 키워드를 추출한다. 본 연구에서는 추출된 AI 키워드 데이터를 PLS 회귀 모형으로 분석한다. 바이오정보학, 사회과학 및 공학 등 다양한 분야에서 고급 데이터 분석을 위하여 사용되는 PLS 회귀 모형은 부분 최소 제곱 기법을 기반으로 한다. 제안 방법의 성능을 확인하기 위하여 AI 특허 문서를 사용하여 분석 실험을 수행하고 제안하는 연구가 실제 문제에 어떻게 적용될 수 있는지 보여 준다. 본 논문은 AI 기술뿐만 아니라 다른 기술 분야에도 적용 할 수 있다. In this paper, we propose an artificial intelligence(AI) technology analysis using partial least square(PLS) regression model. AI technology is now affecting most areas of our society. So, it is necessary to understand this technology. To analyze the AI technology, we collect the patent documents related to AI from the patent databases in the world. We extract AI technology keywords from the patent documents by text mining techniques. In addition, we analyze the AI keyword data by PLS regression model. This regression model is based on the technique of partial least squares used in the advanced analyses such as bioinformatics, social science, and engineering. To show the performance of our proposed method, we make experiments using AI patent documents, and we illustrate how our research can be applied to real problems. This paper is applicable not only to AI technology but also to other technological fields. This also contributes to understanding other various technologies by PLS regression analysis.

Patents on Artificial Intelligence in Asian Countries

위서연,김윤경,김정욱 한국APEC학회 2024 Journal of APEC Studies Vol.16 No.1

This study analyzes trends in industries utilizing artificial intelligence (AI) by examining AI-related patents. The analysis used patents searched from the international patents registry and related to AI technologies. Key information such as patent title, abstract, country, and application dates were utilized. The patent search period was from 2011 to 2023. The study reveals a significant increase in AI-related patents, particularly in major Asian countries, with Korea, China, and Japan leading in contributions. The proportion of patents from Korea has steadily increased, indicating growing global attention to South Korea's AI technologies. Although patents from other countries including China are increasing, South Korea's growth rate is faster, and the citation rate is higher, indicating expectations for the future application of technological developments. The study highlights the expanding role of AI in various sectors, including manufacturing, healthcare, finance, and content creation, reflecting the broad potential of AI technologies in transforming these industries.

인공지능 기술 랜드스케이프 : 기술 구조와 기업별 경쟁우위

이왕재,이학연 한국기술혁신학회 2019 기술혁신학회지 Vol.22 No.3

This study analyzes the technological structure of artificial intelligence (AI) and technological capabilities of AI companies based on patent information. 2589 AI patents registered in USPTO from 2007 to 2017 were collected and analyzed by the Latent Dirichlet Allocation (LDA) to derive 20 AI technology topics. Analysis of technology development trends by AI technology reveals that visual understanding, data analysis, motion control, and machine learning are growing, while language understanding and speech technology are sluggish. In addition, we also investigated leading companies in each sub-field of AI as well as core competencies of global IT companies. The findings of this study are expected to be fruitfully used for formulation and implementation of technology strategy of AI companies. 본 연구는 특허 데이터를 활용하여 인공지능 기술의 구조를 파악하고 주요 글로벌 IT 기업들의 인공 지능 기술역량을 분석한다. 2007년부터 2017년까지 미국 특허청에 등록된 2,589개의 인공지능 특허를 바탕으로 LDA 토픽모델링을 수행하여 인공지능 분야의 20개의 기술 토픽을 도출하였다. 인공지능 기 술 분야 중 언어이해, 음성처리보다는 시각이해, 데이터분석, 동작제어, 그리고 기계학습 분야의 연구 개발이 최근 활발한 것으로 나타났다. 또한 기업별 인공지능 기술 역량을 분석하여 인공지능 기술 분야 별로 우수 역량을 보유한 기업을 도출하고, 기업별로 강점을 가지고 있는 세부 기술 분야를 도출하였 다. 본 연구 결과는 인공지능 기업들의 기술기획 및 전략 수립에 유용하게 활용될 수 있을 것으로 기대 된다.

인공지능 특허에 대한 시계열 기반의 동적 토픽 분석 및 미래 키워드 예측

황진경,송혜령,유동희 한국인터넷전자상거래학회 2024 인터넷전자상거래연구 Vol.24 No.4

This paper aims to conduct a future keyword prediction study by applying dynamic topic modeling and the VAR model through time series analysis using artificial intelligence-related patent data from 2012 to 2022. Patent data was collected through the KIPRIS platform, and major keywords such as ‘information’, ‘data’, and ‘user’ were constantly dealt with in the annual topic trend graph derived through dynamic topic modeling, and the importance of topics such as ‘image’ and ‘video’ has been increasing in recent years. These results suggest that research trends in various application fields are changing with the development of artificial intelligence technology. Next, 10, 20, and 30 top keywords were extracted respectively from the yearly patent data collected for future keyword prediction using BoW, TF-IDF, and Word2Vec, which are three embedding methods. It was confirmed that ‘information’, ‘data’, ‘user’, ‘device’, and ‘system’ were the same important keywords in the annual top keyword analysis by year. The ranking of different patterns was subsequently shown for each embedding method. After that, an experiment was conducted to compare the keywords predicted through the VAR model with the actual 2023 keywords, and it was confirmed that the Word2Vec embedding method showed the highest prediction performance, and the overall performance improved as the number of keywords increased. This study provided important basic data for predicting technology trends and future trends through artificial intelligence patent data, and it is expected that it can be used as a basis for strategic use directions and investment decisions for various stakeholders such as companies, research institutes, and the government.

특허분석을 통한 인공지능 기술 분야 경쟁력 분석:특허 시장성과 기술력 질적 분석을 중심으로

곽현,이성원 한국정보시스템학회 2019 情報시스템硏究 Vol.28 No.3

Purpose Artificial Intelligence (AI) is a core technology, leading the 4th industrial revolution. This study aims to diagnose the Korean's national competitiveness for AI technologies through patent analyses. Design/methodology/approach In this study, KIWEE and Derwent Innovation databases were used as data source of patents. we extracted 10,510 AI patents data with keywords and classified them into 15 subcategories of AI technology. We executed patent analyses for activity index, patent intensity index, technology strength, and patent family size and diagnosed Korea's national competitiveness in AI industry. Findings The results showed that Korea is less competitive than the United States and Japan in AI industry. However, patent amount has increased since 2010, which is encouraging result. This study has implication on the need for human and R&D investment in AI industry.