• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.77-84
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• 2016

In general statistical analysis, we need to make a normal assumption. If this assumption is not satisfied, we cannot expect a good result of statistical data analysis. Most of statistical methods processing the outlier and noise also need to the assumption. But the assumption is not satisfied in big data because of its large volume and heterogeneity. So we propose a methodology based on box-plot and data smoothing for controling outlier and noise in big data analysis. The proposed methodology is not dependent upon the normal assumption. In addition, we select patent documents as target domain of big data because patent big data analysis is a important issue in management of technology. We analyze patent documents using big data learning methods for technology analysis. The collected patent data from patent databases on the world are preprocessed and analyzed by text mining and statistics. But the most researches about patent big data analysis did not consider the outlier and noise problem. This problem decreases the accuracy of prediction and increases the variance of parameter estimation. In this paper, we check the existence of the outlier and noise in patent big data. To know whether the outlier is or not in the patent big data, we use box-plot and smoothing visualization. We use the patent documents related to three dimensional printing technology to illustrate how the proposed methodology can be used for finding the existence of noise in the searched patent big data.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.1
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• pp.7-12
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• 2013

In this paper, we provide a basic data to constitute knowledge map through analysis of competition situation such as analysis of patent activity for each nationality, analysis of patent activity for each applicant for a patent, analysis of patent activity for each technical area and analysis of competition status for power of security for market which consider qualitative level. In order to analysis LED data, we choose patent data of LED.

• Journal of Information Technology Services
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• v.21 no.6
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• pp.39-51
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• 2022

As the 4th Industrial Revolution emerged as a key to improving national competitiveness, OCR technology, one of the major technologies in the 4th industry is in the spotlight. Since characters in various images contain a lot of information, OCR technology for recognizing these characters has evolved into technology used in many industries. In this paper, trends in OCR technology were identified and predicted using thesis data published in 'RISS' and patent data by International patent classification (IPC) under the theme of Optical character recognition (OCR). For patent data 20,000 patents related to OCR technology from 2002 to 2020 were used as data, and 432 papers from 2012 to 2022 were used as data. Through time-series analysis, each patent data and thesis data were investigated since when OCR technology has developed, and various keyword analysis predicted which technology will be used in the future. Finally, the direction of future OCR technology development was presented through network association analysis with patent data and thesis data.

• Korean Management Science Review
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• v.28 no.2
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• pp.63-74
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• 2011

As business environment has become more competitive, the R&D strategies of firms have been regarded more important. Patent has information about technology which affects a firm's profit and it is considered as resources which have provided appropriate data for research of innovations and trends in technology. And patent indicators are known as qualitative representation of technology quality in an objective view. Also, they are available for the continuous and systematic analysis. However, most previous studies have focused on developing patent indicators to investigate patent value and characteristics. Furthermore they have limitations that most results is not significant that patent indicators have effect on firm performance-Tobin's q, Intangible assets based on balance sheet, sales and etc. Thus, the purpose of this paper is to propose proper a factor to represent a firm performance and to analyze causal relationship between patent indicators and firm performance. Intangible assets based on market value are employed as one of most significant firm performance indicator. The results indicate that intangible assets are appropriate for analyzing causal relation between patent and a firm performance with 7 significant indicators among 10 patent indicators. Considering firm's exogenous factors, regression analysis of each data for five years is performed. This result is similar to regression analysis of full data for all years.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.179-186
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• 2017

Technology forecasting is predict future trend and state of technology by analyzing the results so far of developing technology. In general, a patent has novel information about the result of developed technology, because the exclusive right of technology included in patent is protected for a time period by patent law. So many studies on the technology forecasting using patent data analysis has been performed. The patent keyword data widely used in patent analysis consist of occurred frequency of the keyword. In most previous researches, the continuous data analyses such as regression or Box-Jenkins Models were applied to the patent keyword data. But, we have to apply the analytical methods of discrete data for patent keyword analysis because the keyword data is discrete. To solve this problem, we propose a patent analysis methodology using Bayesian Poisson discrete model. To verify the performance of our research, we carry out a case study by analyzing the patent documents applied by Apple until now.

• Journal of the Korea Convergence Society
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• v.9 no.2
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• pp.251-257
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• 2018

As the use of big data is necessary for increasing business value, the size of the big data market is getting bigger. Accordingly, it is important to apply competitive patents in order to gain the big data market. In this study, we conducted the patent analysis based keyword network to analyze the trend of big data patents. The analysis procedure consists of big data collection and preprocessing, network construction, and network analysis. The results of the study are as follows. Most of big data patents are related to data processing and analysis, and the keywords with high degree centrality and between centrality are "analysis", "process", "information", "data", "prediction", "server", "service", and "construction". we expect that the results of this study will offer useful information in applying big data patent.

• The Journal of Information Systems
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• v.28 no.3
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• pp.141-158
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• 2019

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.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.143-149
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• 2022

Since patent documents contain detailed results of research and development technologies, many studies on various patent analysis methods for effective technology analysis have been conducted. In particular, research on quantitative patent analysis by statistics and machine learning algorithms has been actively conducted recently. The most used patent data in quantitative patent analysis is technology keywords. Most of the existing methods for analyzing the keyword data were models based on the Gaussian probability distribution with random variable on real space from negative infinity to positive infinity. In this paper, we propose a model using gamma probability distribution to analyze the frequency data of patent keywords that can theoretically have values from zero to positive infinity. In addition, in order to determine the regression equation of the gamma-based regression model, two-mode network is constructed to visualize the technological association between keywords. Practical patent data is collected and analyzed for performance evaluation between the proposed method and the existing Gaussian-based analysis models.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.121-137
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• 2013

Now days, firm's technology capability is recognized as important factor to forecast and to evaluate firm's business performance. There are many efforts to develop useful indicators by applying patent information that includes concrete description about technology. Many previous studies analyzed relationship between patent indicators and firm's performance. But they didn't consider time gap between a point of firm's invention activity and a point of firm's performance improvement. They didn't considered a character of industrial fields either. To overcome these limitations, we selected IT industry for target analysis industry. Time-series patent data and financial data from 41 American IT firms between 2000 and 2011 were used to analyze. In this study, We empirically analyzed subsequent effect of patent indicators on firm's business performance by using correlation analysis and regression analysis.

• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.125-145
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• 2020

We explore technology ecosystem of smart surgical medical system by analyzing patent data applied for in Korea and Japan. First, a review of trends of patent application by country/technological domain show that there exist a minority of technology domains focused on R&D, which represent their trends have been increasingly active. Also, while a number of Japanese firms mainly consist of the patent market of Japan, in case of the Korean market, a few universities, SMEs, and foreign firms are found to be the main applicants. As a result of the network analysis with the links as the relations of co-patenting, the relationships, which are active of convergence and knowledge spillover among the heterogeneous technology domains within each market, as well as the technology domains, which are the most active in international cooperation among each homogeneous domain, could get derived and visualized in the ecosystem. In addition, the technology domains in each patent market with leading locations, roles, and influence in the network can also be identified through the centrality analysis. In this study, the analysis for technology competitiveness are carried out focusing on patent activity and patent impact. The results denote that across all domains, the Japanese market may possess higher patent activity and patent impact compared to the Korean market. In consequence, we derive the position map for comparison by country and technology domain from a perspective considering comprehensively the multi-dimensional attributes based on the results of both network analysis and technology competitiveness.