• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.17-30
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• 2015

Technology-oriented national R&D programs produce intellectual property as their final result. Patents, as typical industrial intellectual property, are therefore considered an important factor when evaluating the outcome of R&D programs. Among the main components of patent evaluation, in particular, the patent right quality is a key component constituting patent value, together with marketability and usability. Current approaches for patent right quality evaluation rely mostly on intrinsic knowledge of patent attorneys, and the recent rapid increase of national R&D patents is making expert-based evaluation costly and time-consuming. Therefore, this study defines a hierarchy of patent right quality and then proposes how to quantify the evaluation process of patent right quality by combining text mining and regression analysis. This study will contribute to understanding of the systemic view of the patent right quality evaluation, as well as be an efficient aid for evaluating patents in R&D program assessment processes.

• Journal of the Korea Safety Management & Science
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• v.16 no.1
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• pp.213-220
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• 2014

This study suggests new approach to identify core technologies through patent analysis. Specially, the approach applied data mining technique and multi-criteria decision making method to the co-classification information of registered patents. First, technological interrelationship matrices of intensity, relatedness, and cross-impact perspectives are constructed with support, lift and confidence values calculated by conducting an association rule mining on the co-classification information of patent data. Second, the analytic network process is applied to the constructed technological interrelationship matrices in order to produce the importance values of technologies from each perspective. Finally, data envelopment analysis is employed to the derived importance values in order to identify priorities of technologies, putting three perspectives together. It is expected that suggested approach could help technology planners to formulate strategy and policy for technological innovation.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.21-33
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• 2022

Purpose: As most defense technologies are classified as confidential, the corresponding International Patent Classifications (IPCs) require special attention. Consequently, the list of defense-related IPCs has been managed by the government. This paper aims to evaluate the defense-related IPCs and propose a methodology to revalidate and improve the IPC classification scheme. Methods: The patents in military technology and their corresponding IPCs during 2009~2020 were utilized in this paper. Prior to the analysis, patents are divided into private and public sectors. Social network analysis was used to analyze the convergence structure and central defense technology, and association rule mining analysis was used to analyze the convergence pattern. Results: While the public sector was highly cohesive, the private sector was characterized by easy convergence between technologies. In addition, narrow convergence was observed in the public sector, and wide convergence was observed in the private sector. As a result of analyzing the core technologies of defense technology, defense-related IPC candidates were identified. Conclusion: This paper presents a comprehensive perspective on the structure of convergence of defense technology and the pattern of convergence. It is also significant because it proposed a method for revising defense-related IPCs. The results of this study are expected to be used as guidelines for preparing amendments to the government's defense-related IPC.

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.325-328
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• 2009

Recently, as importance of knowledge property right is rising, a patent is being issue. A patent is exclusive rights of knowledge or technique, and it must be registered for approval of rights. Therefore, prediction of patent registration can be important information for company or individuals which gain profit using a patent. In this paper, we proposed a method for prediction of patent registration using text mining and a algorithm for constructing database.

• Patent21
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• s.89
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• pp.2-15
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• 2010

본 연구보고서는 Text Mining 가법을 기반으로 영문 특허텍스트 DB를 구성하는 텍스트 (Text) 부분의 경제성 및 피검색성을 정량적으로 평가하는 모델을 제시하고， 이를 바탕으로 2차 가공된 영문 특허텍스트 DB의 성능을 일정범위 내에서 관리하는 품질관리모델의 개발 가능성을 탐색하는데 그 목적이 있다.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.88-95
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• 2017

As the safety fields are expanding to a variety of industrial fields, safety technology has been developed by convergence between industrial safety fields such as mechanics, ergonomics, electronics, chemistry, construction, and information science. As the technology convergence is facilitating recently advanced safety technology, it is important to explore the trends of safety technology for understanding which industrial technologies have been integrated thus far. For studying the trends of technology, the patent is considered one of the useful sources that has provided the ample information of new technology. The patent has been also used to identify the patterns of technology convergence through various quantitative methods. In this respect, this study aims to identify the convergence patterns and fields of safety technology using association rule mining(ARM)-based patent co-classification(co-class) analysis. The patent co-class data is especially useful for constructing convergence network between technological fields. Through linkages between technological fields, the core and hub classes of convergence network are explored to provide insight into the fields of safety technology. As the representative method for analyzing patent co-class network, the ARM is used to find the likelihood of co-occurrence of patent classes and the ARM network is presented to visualize the convergence network of safety technology. As a result, we find three major convergence fields of safety technology: working safety, medical safety, and vehicle safety.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.1
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• pp.39-48
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• 2017

In a digital economy, users actively express their needs in many ways. Thus, many researchers analyze what users need and whether they are satisfied or not through opinion mining. In addition, they begin to find technology opportunities in heterogeneous technology fields. But they did not connect users' opinion to technology development process, only focused on natural language processing or marketing or manufacturing area. Also, heterogeneous technology fields are focused on fusion technology. Thus, this study suggests a novel approach that is based on sentimental value and can be applied to exploring technology opportunities in heterogeneous fields. Sentimental value is calculated from users' opinion through sLDA. The heterogeneous technology opportunity is explored by patent analysis. This research contributes to suggesting a hybrid methodology through patent and users' opinion. In addition, it can provide managerial efficiency by suggesting base data onto decision making.

• 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 Korean Society for Quality Management
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• v.49 no.1
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• pp.97-112
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• 2021

Purpose: The purpose of this paper is to analyze the technology convergence and its characteristics, focusing on the defense technologies in South Korea. Methods: Patents applied by the Agency for Defense Development (ADD) during 1979~2019 were utilized in this paper. Information Entropy analysis has been conducted on the patents to analyze the usability and potential for development. To analyze the trend of technology convergence in defense technologies, Social Network Analysis(SNA) and Association Rule Mining Analysis were applied to the co-occurrence networks of International Patent Classification (IPC) codes. Results: The results show that sensor, communication, and aviation technologies played a key role in recent development of defense science and technology. The co-occurrence network analysis also showed that the convergence has gradually enhanced over time, and the convergence between different technology sectors largely emerged, showing that the convergence has been diversified. Conclusion: By analyzing the patents of the defense technologies during the last 30 years, this study presents the comprehensive perspectives on trends and characteristics of technology convergence in defense industry. The results of this study are expected to be used as a guideline for decision making in the government's R&D policies in defence industry.

• The Journal of Information Systems
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• v.30 no.3
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• pp.201-216
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• 2021

Purpose The purpose of this study is to analyze the trend of patent technology in textile materials using text mining methodology based on Dynamic Embedded Topic Model and Structural Topic Model. It is expected that this study will have positive impact on revitalizing and developing textile materials industry as finding out technology trends. Design/methodology/approach The data used in this study is 866 domestic patent text data in textile material from 1974 to 2020. In order to analyze technology trends from various aspect, Dynamic Embedded Topic Model and Structural Topic Model mechanism were used. The word embedding technique used in DETM is the GloVe technique. For Stable learning of topic modeling, amortized variational inference was performed based on the Recurrent Neural Network. Findings As a result of this analysis, it was found that 'manufacture' topics had the largest share among the six topics. Keyword trend analysis found the fact that natural and nanotechnology have recently been attracting attention. The metadata analysis results showed that manufacture technologies could have a high probability of patent registration in entire time series, but the analysis results in recent years showed that the trend of elasticity and safety technology is increasing.