• Journal of Korea Society of Industrial Information Systems
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• v.23 no.3
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• pp.87-95
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• 2018

Recently, with the technological development of artificial intelligence, related market is expanding rapidly. In the artificial intelligence technology field, which is still in the early stage but still expanding, it is important to reduce uncertainty about research direction and investment field. Therefore, this study examined technology trends using text mining and topic modeling among big data analysis methods and suggested trends of core technology and future growth potential. We hope that the results of this study will provide researchers with an understanding of artificial intelligence technology trends and new implications for future research directions.

• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.785-790
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• 2019

Convergence and advancement between technologies such as Artificial Intelligence, Big Data, and the Internet of Things have a significant impact on the regional flagship industry. All technical fields are used as a converged technology by connecting between technology and industry. In order to understanding the recent technical trend, it is possible to easily realized the technical trend research and analysis through keyword search using patent information. The purpose of this study is to identify patent trends applied to convergence technology in the 4th Industrial Revolution age in radiation technology development and to present patent trends and analysis for strengthening and utilizing radiation-related industrial technology competitiveness and to apply them to demand technology and forecast future promising technologies.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.433-437
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• 2010

Patent contains meaningful technical achievement. There are many cases explaining technology trends from the analysis of frequency of term. Term sometimes has different meaning on fields. In this paper, words from patent titles of US, Japan, Korea PCT and EPO are collected by the 5 categories of WIPO. Frequency changes rate of each word were calculated and high ranked words of 5 categories were analyzed to find relationship between patent and technology development as well as technology trends.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.188-192
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• 2007

This paper presents a current perspective on advanced fusion research trends in the construction industry as reflected in the proceedings of International Symposium on Automation and Robotics in Construction (ISARC) which has focused on advanced fusion technology in last decades. The paper reports the results of a 7-year analysis of papers between 2000 and 2006. The analysis focused on such data as research topics of the proceedings. The paper summarizes the data extracted from the paper and uses it to analyze advanced fusion research trends. The research result shows that the top research topics in advanced fusion research areas are construction robots and automation and intelligent construction management. The research also found that research related to advanced fusion technology is increasing throughout the world and topics are changing as current needs change.

• Electronics and Telecommunications Trends
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• v.34 no.2
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• pp.29-39
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• 2019

The interest in facial recognition technology has been growing with the advancement of AI technology. With a confirmed accuracy of over 99%, the areas of application of the technology have expanded, including smartphone unlocking, online payment authorization, building access management, and criminal apprehension. This indicates that the technology has effectively transitioned from laboratory to field applications. This study performs patent analysis to determine recent innovations and diffusion trends in facial recognition technology. Specifically, R&D activities involving facial recognition technology are investigated at both the country level and company level. Significant patents are also considered. This study contributes to R&D management teams by proposing useful plans and strategies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.12
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• pp.1868-1875
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• 2016

This paper presents the mega trends of technology and competitiveness analysis results based on patent analysis for establishing effective research and development (R&D) strategy on UAV (Unmanned Aerial Vehicle) in the aerial ICT industry. In order to analyze mega trends of UAV technologies, patent analysis is conducted focusing on published/registered patents of Korea, the U.S., Japan, and Europe. We divided the target technologies into 3 main category levels based on the converging technology of UAV and ICT. The 3,433 patents are collected. Patent indicators such as patent activity (PA), cites per patent (CPP), and major market expansion (MME) are extracted for grasping the technology competitiveness and Korea's competitiveness per sub category levels of UAV. We suggest the R&D strategy of each technology areas based on patent analysis results. We analyzed Korea's technology levels, advanced companies' R&D trends, and patent trends through patent information and expected that this paper would be utilized for establishment of R&D strategy of UAV in the future.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.2
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• pp.63-73
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• 2018

Academia and research institutes mainly use qualitative methods that rely on expert judgments to understand and predict research trends and science and technology trends. Since such a technique has the disadvantage of requiring much time and money, in this study, science and technology trends were predicted using keyword network analysis. To that end, 13,618 AI (Artificial Intelligence) patent abstracts were analyzed using keyword network analysis in three separate lots based on the period of the submission of each abstract: analysis period 1 (January 1, 2002 - December 31, 2006), analysis period 2 (January 1, 2007 - December 31, 2011), and analysis period 3 (January 1, 2012 - December 31, 2016). According to the results of frequency analyses, keywords related to methods in the field of AI application appeared more frequently as time passed from analysis period 1 to analysis period 3. In keyword network analyses, the connectivity between keywords related to methods in the field of AI application and other keywords increased over time. In addition, when the connected keywords that showed increasing or decreasing trends during the entire analysis period were analyzed, it could be seen that the connectivity to methods and management in the field of AI application was strengthened while the connectivity to the field of basic science and technology was weakened. According to analysis of keyword connection centrality, the centrality value of the field of AI application increased over time. According to analysis of keyword mediation centrality during analysis period 3, keywords related to methodologies in the field of AI application showed the highest mediation value. Therefore, it is expected that methods in the field of AI application will play the role of powerful intermediaries in AI hereafter. The technique presented in this paper can be employed in the excavation of tasks related to regional innovation or in fields such as social issue visualization.

• International Journal of Contents
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• v.12 no.3
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• pp.54-58
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• 2016

In this study, articles of the science and technology field that had been monitored for the period from 2002 to 2013 using GTB (Global Trends Briefing) were analyzed. Specifically, the VOSviewer was used to analyze the annual science and technology trends by keyword and the science and technology standard-classification information indicated in the GTB articles, and the convergence trends were therefore monitored. The findings of this study show that active studies were under way in the fields of material science and new and renewable energy, and that convergence has progressed. This result indicates that the information of the articles on papers and patents is more reliable, as it can reflect the current trends more rapidly in the science and technology field than the paper information or the patent information that is traditionally used in analyses of science and technology information.

• Smart Structures and Systems
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• v.29 no.2
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• pp.361-374
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• 2022

As civil infrastructure has continued to age worldwide, its structural integrity has been threatened owing to material deteriorations and continual loadings from the external environment. Structural Health Monitoring (SHM) has emerged as a cost-efficient method for ensuring structural safety and durability. As SHM research has gradually addressed an increasing number of structure-related problems, it has become difficult to understand the changing research topic trends. Although previous review papers have analyzed research trends on specific SHM topics, these studies have faced challenges in providing (1) consistent insights regarding macroscopic SHM research trends, (2) empirical evidence for research topic changes in overall SHM fields, and (3) methodological validations for the insights. To overcome these challenges, this study proposes a framework tailored to capturing the trends of research topics in SHM through a bibliometric and network analysis. The framework is applied to track SHM research topics over 15 years by identifying both quantitative and relational changes in the author keywords provided from representative SHM journals. The results of this study confirm that overall SHM research has become diversified and multi-disciplinary. Especially, the rapidly growing research topics are tightly related to applying machine learning and computer vision techniques to solve SHM-related issues. In addition, the research topic network indicates that damage detection and vibration control have been both steadily and actively studied in SHM research.

• 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.