• The KIPS Transactions:PartB
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• v.16B no.3
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• pp.225-232
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• 2009

Author name disambiguation is essential for improving performance of document indexing, retrieval, and web search. Author name disambiguation resolves the conflict when multiple authors share the same name label. This paper introduces a novel approach which exploits ontologies and WordNet-based category utility for author name disambiguation. Our method utilizes author knowledge in the form of populated ontology that uses various types of properties: titles, abstracts and co-authors of papers and authors' affiliation. Author ontology has been constructed in the artificial intelligence and semantic web areas semi-automatically using OWL API and heuristics. Author name disambiguation determines the correct author from various candidate authors in the populated author ontology. Candidate authors are evaluated using proposed WordNet-based category utility to resolve disambiguation. Category utility is a tradeoff between intra-class similarity and inter-class dissimilarity of author instances, where author instances are described in terms of attribute-value pairs. WordNet-based category utility has been proposed to exploit concept information in WordNet for semantic analysis for disambiguation. Experiments using the WordNet-based category utility increase the number of disambiguation by about 10% compared with that of category utility, and increase the overall amount of accuracy by around 98%.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.2
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• pp.197-223
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• 2020

In this study, citation-weighted author profiling (CWAP) was developed as a new method that combines the advantages of both author profiling (AP) method and author co-citation analysis (ACA) method. In AP method, words reflect the author's main topics of study. On the other hand, what words reflect in CWAP is topics that the author mainly influences. This enables detailed topic identification, which is the advantage of AP method, and at the same time determines the subjects in which the author has influence, as with ACA method. The proposed CWAP method was applied experimentally to analyze the intellectual structure of school library research in Korea. The results of the trial application revealed in detail what topics each author has a high influence on, and the change of influence over time was also clearly revealed. The CWAP method proposed in this study is expected to be used as a technique to grasp detailed topics from the viewpoint of research influence on which topics the author has been cited for, not as a research productivity perspective of how many papers the author has published.

• Journal of Technologic Dentistry
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• v.34 no.1
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• pp.45-56
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• 2012

Purpose: This study reviews the recent trend of Korean Academy of dental technology research. The data examined are the articles published in the Korean Journal of Korean Academy of dental technology from 1979 to 2011. Methods: The data are retrieved through the internet database Korean Academy of dental technology. The number of paper published is 540, published in 33 volumes of the journal. This study examines research methods, subjects, and author information. Results: Among the 540 articles collected, 422 are Original papers, 106 Clinical Technical Papers, 12case Other papers. 235 are experimental studies. Most experimental studies(235) have examined the ceramic(Porcelain) parts(117). The sole author of 315, co-author of 225 appeared. In turn of dental technicians, and students appeared. Conclusion: The study is to present basic data for research and to indicate the direction of their study in the future.

• The Journal of Information Systems
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• v.28 no.3
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• pp.39-58
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• 2019

Purpose A digital twin is a digital replication of a physical system. Gartner identified the digital twin as one of the Gartner Top 10 Strategic Technology Trend for three years from 2017. The rapid development of the digital twin market is expected to bring about innovation and change throughout society, and much research has been done recently in academia. In this research, we tried to explore the main research trends for digital twin research. Design/methodology/approach We collected the digital twin research from Web of Science, and analyzed 804 articles that was published during time span of 2010-2018. A total of 41 key authors were selected based on the frequency of citation. We created a co-citation matrix for the core authors, and performed multivariate analysis such as cluster analysis and multidimensional scaling. We also conducted social network analysis to find the influential researchers in digital twin research. Findings We identified four major sub- areas of digital twin research: "Infrastructure", "Prospects and Challenges", "Security", and "Smart Manufacturing". We also identified the most influential researchers in digital twin research: Lee EA, Rajkumar R, Wan J, Karnouskos S, Kim K, and Cardenas AA. Limitation and further research suggestion were also discussed as a concluding remarks.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.468-472
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• 2007

There are many measuring tools to evaluate individual's scientific productivity using scientific articles based on bibliometrics. Especially succeeding discussions are accomplished at an trial for individual's scientific productivity after Hirsch's 2005 proposal using h-index. And there are many succeeding discussions and applications to evaluate journals, articles and qualitative level of researchers using h-index, g-index. But these indices have a same indices without regard to first author or other co-author if a article has a same number of citations. This research aims to propose K-index integrated between these indices and author rank.

• Journal of the Korean Society for information Management
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• v.39 no.2
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• pp.203-232
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• 2022

Drug addiction or substance use disorder is continuously observed worldwide for its risks and prevalence. In this context, numerous studies have been conducted regarding this issue. However, bibliometric analysis related to drug addiction is insufficient. In particular, it is difficult to find research that utilizes a macro-level bibliographic approach that comprehensively reflects various characteristics related to drug addiction. In this study, to reflect the multidimensional features of drug addiction, research trends in drug addiction in social science, natural science, and multidisciplinary studies were compared and analyzed. This study collected drug addiction research articles from 2002 to 2021 by searching from the Web of Science, and classified academic disciplines based on SCI(E) and SSCI information. Author keyword co-occurrence analysis was also conducted, which provided confirmation that natural science mainly studied psychoactive substances and the reward system in the brain, while drug addiction studies reflecting demographic characteristics were conducted in the domain of social science. In the multidisciplinary field, all of the above topics were covered. Author co-citation analysis was also employed, which showed that there are superstars (i.e., authors who receive a rigorous amount of citation) in the field of natural science, while in the social science domain, authors were highly cited not only at the individual level but also at the institutional level.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.239-259
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• 2022

Since 2019, research on microplastics has been actively conducted around the world, so analyzing the differences between domestic and foreign microplastics research can be a milestone in establishing the direction of domestic research. In this study, microplastic papers from KCI and WoS were extracted and the differences between domestic and foreign studies were analyzed using a network analysis methodology based on big data such as author keyword co-occurrence word analysis, thesis co-citation analysis, and author co-citation analysis. As a result of the analysis, the analysis of the research topic confirmed that studies that could affect the human body and the treatment of microplastics in daily life were additionally needed in Korea. In the analysis of the depth of thesis citation that examines the quality of research, it was found that Korea was still insufficient at 2.25 overseas and 1.39 in Korea. In the analysis of the composition of the joint research front, where various researchers participate and share information, 3 out of 22 clusters in Korea are Star type. In the case of overseas, all 19 clusters have a mesh structure, so it was confirmed that information flow and sharing were insufficient in specific research fields in Korea. These research results confirmed the need to expand the research topic of microplastics, improve the quality of research, and improve the research promotion system in which various researchers participate. In addition, if the automation program is developed based on topic modeling, it will be possible to build a system capable of real-time analysis.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2011.05a
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• pp.5-6
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• 2011

CO₂ reduction is the most urgent issue the world is facing. So, there should be a measure to reduce the CO₂ emission in construction industry which has more released CO₂ gas than other industries. CO₂ emission of building depend on using energy. Then efficient energy use process working efficiently at CO₂ reduction. Therefore In this study, author find the technical possibility of saving the building energy using the PCM which is able to control heat, storage heat and potential heat. So, it considered that apply to floor heating type which is major heating system of living space in Korea. And evaluate the Using possibility.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.148-150
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• 2017

In recent years, "altmetrics", given birth by social media and the academic community, have become a metric source for measuring the academic impact of scientific literature. This study has undertaken a co-word analysis of author keywords in "Altmetrics" articles from the Web of Science database from 2012 to 2017 and used a co-occurrence matrix to create a clustering of the words. "Altmetrics" co-occurrence network map was derived and the research hotspots was analyzed.

• Journal of the Korean Society for information Management
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• v.34 no.2
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• pp.7-26
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• 2017

There has been growing interest in the methods for measuring the credits of individual authors in multi-authored research papers in response to the increase of research collaboration. Having a good understanding for academic norms of individual discipline is essential to measure author credit effectively. However, many Korean universities do not consider different norms for determining the order of authors across disciplines. Rather, they tend to use a standardized method to assess the credits of authors in multi-authored papers. Therefore, this study presented some problems of applying a standardized method to measure author credits in multi-authored papers in economics. The findings of this study confirmed the frequent use of alphabetical author order in economics papers; however, many university guidelines for research evaluation do not take account the alphabetical authorship in measuring the credits of authors. The authors suggest the needs for (1) establishment of a clear definition for primary authors, (2) flexibility in assessment methods for author credit, and (3) empirical research on author credit.