• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.103-106
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• 2007

The importance of intellectual property right becomes larger and the number of the person who uses a patent search is increasing. When considering the search pattern of the general user who uses only one or two search terms, it is not easy task to find desirable search result in the massive patent documents. So we present patent search system based on IPC Clustering which helps users confine the search result by using international patent classification (IPC) which provided from all patent documents. By using this system, the general users can find patent search result more effectively.

• The Journal of the Korea Contents Association
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• v.20 no.6
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• pp.1-8
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• 2020

The use of text data in big data analytics has been increased. So, much research on methods for text data analysis has been performed. In this paper, we study Bayesian learning based on conjugate prior for analyzing keyword data extracted from text big data. Bayesian statistics provides learning process for updating parameters when new data is added to existing data. This is an efficient process in big data environment, because a large amount of data is created and added over time in big data platform. In order to show the performance and applicability of proposed method, we carry out a case study by analyzing the keyword data from real patent document data.

• 발명특허
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• v.32 no.3 s.368
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• pp.36-39
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• 2007

두바이의 실험 모델은 향후 세계곳곳에서 벌어질 일이 될 것이다. 초고층 건축기술과 IT 기술을 접목하면 우리가 가장 경쟁력을 가지고 세계를 석권할 수 있는 분야가 될 것이다. 조선 항공우주 로봇 등 향후 유망업종에서 우리의 경쟁력은 무궁 무진하다. 이러한 경쟁력의 원천이 우수한 민족의 두뇌이고 이것을 바탕으로 창의력을 발휘한다면 골드만삭스사가 예측한 GDP는 세계 2위가 될 것이다.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2005.05a
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• pp.249-262
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• 2005

• Journal of the Korean Geographical Society
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• v.44 no.3
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• pp.355-371
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• 2009

The purpose of this study is to investigate the spatial structure of the production of technological knowledge in the Korean photonics industry. Patent data were used as a proxy of knowledge production. The data were gathered by keywords among the registered patents which were applied from 1996 to 2007. The photonics industry patents registered at United States Patent Trademark Office(USPTO) show that Korea and Taiwan, as a latecomer, have rapidly increased. The photonics industry patents registered at Korean Intellectual Property Office(KIPO) were analyzed by type of application: single-applicant and co-applicant patents. The analysis of single-applicant patents shows that technological knowledge in the Korean photonics industry has been produced mainly in Seoul, Suwon, and Daejeon. The degree of spatial bias, however, has been slightly decreased during the study period. Above-mentioned regions are also main centers in the analysis of co-applicant patents, but the forms of inter-regional cluster and network are different over time. It is because agents participating in co-applicant patents are diverse and increased. Furthermore, it seems that policies, such as the improvement of the infrastructure of ICT, the promotion of the photonics industry and the industry-university-institute collaboration, are very influential.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.355-360
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• 2014

Forecasting of emerging technology plays important roles in business strategy and R&D investment. There are various ways for technology forecasting including patent analysis. Qualitative analysis methods through experts' evaluations and opinions have been mainly used for technology forecasting using patents. However qualitative methods do not assure objectivity of analysis results and requires high cost and long time. To make up for the weaknesses, we are able to analyze patent data quantitatively and statistically by using text mining technique. In this paper, we suggest a new method of technology forecasting using text mining and ARIMA analysis.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.43-50
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• 2021

This paper aims to identify trends of domestic industry-academic cooperation through comparative analysis of domestic and overseas academic articles published over the past 10 years (2011-2021). To this end, keyword network analysis and topic modeling analysis were performed to identify the characteristics of the entire articles collected. As results, it turned out that domestic articles included school, employment, education, patent, and professor as a major keyword while for overseas articles, project, policy, innovation, and company were the main topics, and related keywords were found to be influential. These results suggest that domestic industry-academic cooperation would have been designed and led by universities focusing on education for employment, and need to be carried out more actively in the areas of 'research' and 'technology transfer with the government's related policies and support on establishing two-way relationships that can benefit both schools and participating companies.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.650-652
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• 2014

국가와 기업의 연구개발투자 및 경영정책 전략 수립에서 미래 부상기술 예측은 매우 중요한 역할을 한다. 기술예측을 위한 다양한 방법들이 사용되고 있으며 특허를 이용한 기술예측 또한 활발히 진행되고 있다. 최근에는 텍스트마이닝을 이용해 특허데이터의 정량적인 분석이 이루어지고 있다. 본 논문에서는 텍스트마이닝과 지수평활법을 이용한 기술예측 방법을 제안한다.

• Journal of the Korean Society for information Management
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• v.27 no.2
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• pp.7-20
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• 2010

This study aims to provide a method of extracting the most recent information on US patent documents. An HTML paring technique that can directly connect to the US Patent and Trademark Office (USPTO) Web page is adopted. After obtaining a list of 50 documents through a keyword searching method, this study suggested an algorithm, using HTML parsing techniques, which can extract a patent number, an applicant, and the US patent class information. The study also revealed an algorithm by which we can extract both patents and subsequent patents using their closely connected relationship, that is a very distinctive characteristic of US patent documents. Although the proposed method has several limitations, it can supplement existing databases effectively in terms of timeliness and comprehensiveness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3677-3688
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• 2011

The patent information retrieval system can serve a variety of purposes. In general, the patent information is retrieved using limited key words. To identify earlier technology and priority rights repeated effort is needed. This study proposes a method of content-based retrieval using text mining. Using the proposed algorithm, each of the documents is invested with characteristic value. The characteristic values are used to compare similarities between query documents and database documents. Text analysis is composed of 3 steps: stop-word, keyword analysis and weighted value calculation. In the test results, the general retrieval and the proposed algorithm were compared by using accuracy measurements. As the study arranges the result documents as similarities of the query documents, the surfer can improve the efficiency by reviewing the similar documents first. Also because of being able to input the full-text of patent documents, the users unacquainted with surfing can use it easily and quickly. It can reduce the amount of displayed missing data through the use of content based retrieval instead of keyword based retrieval for extending the scope of the search.