• Journal of Information Management
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• v.35 no.1
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• pp.93-112
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• 2004

This study is intend to analyze the cited patent life time of US patent data via more objective way. It is based on exploratory approach which is one of various methods for technology forecasting. The life spans of cited patents of specific technological field are deduced from using informetric analysis of USPA database of KISTI, which is composed of US patent data covered from 1972 to present. The statistics of the results may help to estimate the economic life span of the specific technological area for technology valuation.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1273-1284
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• 2016

In this paper, we analyzed the patents on machine learning using keyword network analysis and clique analysis. To construct a keyword network, important keywords were extracted based on the TF-IDF weight and their association, and network structure analysis and clique analysis was performed. Density and clustering coefficient of the patent keyword network are low, which shows that patent keywords on machine learning are weakly connected with each other. It is because the important patents on machine learning are mainly registered in the application system of machine learning rather thant machine learning techniques. Also, our results of clique analysis showed that the keywords found by cliques in 2005 patents are the subjects such as newsmaker verification, product forecasting, virus detection, biomarkers, and workflow management, while those in 2015 patents contain the subjects such as digital imaging, payment card, calling system, mammogram system, price prediction, etc. The clique analysis can be used not only for identifying specialized subjects, but also for search keywords in patent search systems.

• World Technopolis Review
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• v.3 no.3
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• pp.122-138
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• 2014

The number of environment-related technologies has increased remarkably over the past two decades, as has the public's interest in effective resource use and ways to reduce the effects of global warming. Industries that are based on environment-related technologies are thus growing rapidly. Previous studies revealed that externalities derived from the population concentration in urban areas positively affect agglomerations of high-tech industries. Such externalities have been named the "knowledge spillover effect". The purposes of the present paper are to (1) give a thumbnail sketch of the locations of environment-related industries around the world, using the Organisation for Economic Co-operation and Development environment-related patent statistics, and (2) explicate the effects of the Marshall-Arrow-Romer (MAR) and Jacobs externalities, which result from population concentrations in urban areas, on the agglomeration of environment-related industries in Sweden. The analysis revealed that environment-related industries are located chiefly in urban areas across the globe, and that only the MAR externalities influenced positively on the agglomeration of these industries in Sweden.

• Journal of Technology Innovation
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• v.27 no.2
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• pp.73-98
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• 2019

This study aims to contribute to the improvement of the patent activity of small and medium-sized enterprises in the future by proposing five strategies for enhancing customized patent activity for small and medium-sized enterprises under the assumption that patent application affects firm performance. The subjects of this study were 25 years of active patent activity, using patent activity statistics for 5 years from 2010 and statistical data of business performance based on 2014. The research procedure was conducted in the order of DEA-BCC efficiency analysis, patent activity analysis, and patent portfolio analysis, and then propose a strategy to improve patent activity. As a result of the research, it was confirmed that 5 industries with high patent activity and IRS type have a substantial effect on improving corporate performance as an industry with high patent efficiency. On the other hand, there are 12 industries in the form of IRS/DRS, and 8 industries with low patent activity, DRS, CRS/IRS mixed type and IRS, and that the efficiency of the patent may vary depending on the characteristics of each industry.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.199-211
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• 2009

Official statistics which are collected for governments and the community can be used to assess the effectiveness of governments' policies and programs. Thus, official statistics should be collected and presented based on correct findings. Erroneous official statistics will lead to lower quality results in assessing those policies and programs. Many statistical agencies, today, use on-line analytical processing (OLAP) data cubes which support OLAP tasks like aggregation and subtotals as a key part of their dissemination strategy of official statistics. Confidentiality protection in data cubes also should be made. However, sensitive parts of data cubes including micro data may be disclosed by malicious inferences. The authors have suggested an inference control process in OLAP data cubes which preventing erroneous cube creating and securing cubes against privacy breaches. The objective of this study is to establish a strategy for inference control of official statistics using the inference control process by taking the case of the Patent Application Expense Support Project.

• Asian Journal of Business Environment
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• v.13 no.2
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• pp.21-28
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• 2023

Purpose: This study aims to analyze the determinants of Green Total Factor Productivity (Green TFP) growth in the agricultural sector in Indonesia from 1980-2018. Research design, data, and methodology: The growth of Green TFP in the agricultural sector is calculated using the Growth Accounting Method. Moreover, this study uses multiple linear regression to analyze the determinants of the growth of Green TFP in the agricultural sector in Indonesia. Results: The survey results show that the average growth of Green TFP in the agricultural sector in Indonesia is still negative, which indicates that the efficiency of production factor or mastery of technology is still low. Inflation and patent applications are variables that significantly affect the growth of Green TFP in the agricultural sector, where the inflation variable has a negative effect. In contrast, the variable growth of patent applications has a positive impact. Conclusions: The government needs to continue to improve efficiency by organizing various programs related to increasing mastery of technology in the agricultural sector. The government also needs to advance research and development by promoting patents to become research incentives and impact the improvement of new technologies, especially those related to the environment. Moreover, economic stability needs to be maintained through inflation control.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.67-68
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• 2020

Real-time information on the construction project required by the owner make the project's transparency and overall productivity will be improved. This study analyzes domestic and foreign patents for construction project management to identify trends in technology development, construct cloud-based construction project management system solution UI, and proposes functions and services for each module. Trend research is conducted through patent search, and the analysis is divided into quantitative analysis which means quantitative statistics and qualitative analysis which means the technical contents of each patent. The construction project management system solution is based on smart devices at small and medium-sized sites, allowing both the owner and the construction personnel to share information.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.2
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• pp.111-118
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• 2016

Artificial intelligence (AI) is making computer systems intelligent to do right thing. The AI is used today in a variety of fields, such as journalism, medical, industry as well as entertainment. The impact of AI is becoming larger day after day. In general, the AI system has to lead the optimal decision under uncertainty. But it is difficult for the AI system can derive the best conclusion. In addition, we have a trouble to represent the intelligent capacity of AI in numeric values. Statistics has the ability to quantify the uncertainty by two approaches of frequentist and Bayesian. So in this paper, we propose a methodology of the connection between statistics and AI efficiently. We compute a fixed value for estimating the population parameter using the frequentist learning. Also we find a probability distribution to estimate the parameter of conceptual population using Bayesian learning. To show how our proposed research could be applied to practical domain, we collect the patent big data related to Apple company, and we make the AI more intelligent to understand Apple's technology.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.109-115
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• 2020

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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.471-479
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• 2020

In this paper, we analyze features of radical innovative businesses using their patents. Although patents have been used to evaluate outcomes of businesses from the 1980s, it is challenging to use patents for radical innovations. We examined the possibility of taking advantage of patents for an indicator that represents a radical innovation in pharmaceutical industry. To this end, we collected FDA approval data from the U.S. Food and Drug Administration and patent data of 18 pharmaceutical companies. For analysis, we utilized the network centrality analysis and Wilcoxon signed ranked test, which is a non-parametric statistical hypothesis test used to compare two related samples. We observed that a radical innovative company typically cooperates with other research groups, such as universities and companies, and acts as a hub for connectivity in pharmaceuticals. Also, we found that there are differences in centrality between radical firms and non-radical firms. Thus, we expect that the results of this study will help in developing strategies for research and development of pharmaceutical companies and identifying factors affecting radical innovation in the future.