• The Mathematical Education
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• v.52 no.4
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• pp.483-496
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• 2013

In this study, we investigated the structure of the mathematics education scholars' co-authorship relationship in papers registered at the National Research Foundation of Korea by social network analysis. The data were 354 scholars from 257 papers in 4 journals from 2009 to 2013 based on 'the 2009 revised Korean National Curriculum'. For the analysis, Pajek3 and UCINET6.3 were used. The results of this study were as follows: First, each of the mathematics education scholars is connected on average with about 5 paths of intermediate collaborators. Second, Analyses of the first component group found distinguishable scholar groups' characteristics depending on their affiliations, majors, and job statuses. Third, there were scholars having high values in network degree centrality measures despite not having high numbers in published papers. On the contrary, there sere scholars having high numbers in published papers despite not having high values in network analysis. Finally, I suggested the directions for the future research with the limitations of this study.

• International Journal of Human Ecology
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• v.7 no.1
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• pp.111-119
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• 2006

The purpose of our study is to explore dynamic mechanisms within families and self-authored decisions among Korean female college students. In particular, we investigated how parent-child interactions influence the development of self-authorship and self-authored decisions within Korean culture through interviews with 14 female college students. Results showed unique cultural influences on how female college students interacted with parents and interpreted and reflected parents' opinions in their self-authored decisions. These results suggest further research on gender differences and complex family influences on self-authored decisions within cultural contexts.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.33-41
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• 2018

Recently, Internet technology has developed, various programs are being created and therefore various codes are being made through many authors. On this aspect, some author deceive a program or code written by other particular author as they make it themselves and use other writers' code indiscriminately, or not indicating the exact code which has been used. Due to this makes it more and more difficult to protect the code. In this paper, we propose author identification framework using Authorship Analysis theory and Natural Language Processing(NLP) based on Convolutional Neural Network(CNN). We apply Authorship Analysis theory to extract features for author identification in the source code, and combine them with the features being used text mining to perform author identification using machine learning. In addition, applying CNN based natural language processing method to source code for code author classification. Therefore, we propose a framework for the identification of authors using the Authorship Analysis theory and the CNN. In order to identify the author, we need special features for identifying the authors only, and the NLP method based on the CNN is able to apply language with a special system such as source code and identify the author. identification accuracy based on Authorship Analysis theory is 95.1% and identification accuracy applied to CNN is 98%.

• Journal of Internet Computing and Services
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• v.21 no.2
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• pp.1-8
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• 2020

Recently, the number of APT(Advanced Persistent Threats) attack using malware has been increasing, and research is underway to prevent and detect them. While it is important to detect and block attacks before they occur, it is also important to make an effective response through an accurate analysis for attack case and attack type, these respond which can be determined by analyzing the attack group of such attacks. Therefore, this paper propose a framework based on genetic algorithm for analyzing malware and understanding attacker group's features. The framework uses decompiler and disassembler to extract related code in collected malware, and analyzes information related to author through code analysis. Malware has unique characteristics that only it has, which can be said to be features that can identify the author or attacker groups of that malware. So, we select specific features only having attack group among the various features extracted from binary and source code through the authorship clustering method, and apply genetic algorithm to accurate clustering to infer specific features. Also, we find features which based on characteristics each group of malware authors has that can express each group, and create profiles to verify that the group of authors is correctly clustered. In this paper, we do experiment about author classification using genetic algorithm and finding specific features to express author characteristic. In experiment result, we identified an author classification accuracy of 86% and selected features to be used for authorship analysis among the information extracted through genetic algorithm.

• Journal of vocational education research
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• v.35 no.6
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• pp.85-112
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• 2016

This study aims to identify the cooperative relations among researchers and their network structures based on the academic papers published in the field of lifelong vocational education and training from 2000 to 2015. Authors in three representative journals, 'Journal of Lifelong Education', 'Journal of Vocational Education Research', and 'Korea Research Institute for Vocational Education & Training,' during the periods, were selected and co-authorship network analysis was applied using NetMiner 4.0 in order to find the social relation among researchers and their academic influences. The results showed that the research productivity in the field of lifelong vocational education and training forms a shape of the power function where there exist components called, 'detailed research groups.' This network structure represents characteristics of a small world. In addition, the centrality analysis suggest authors with high centrality serve as co-authors who play as a central role on the network and exchange information with other researchers, while those with high betweenness centrality serve as a channel where they transfer knowledge and information among research groups. Increasing member of co-authorship has positively contributed to the opportunity and development of cooperative research among researchers in the field of lifelong vocational education and training. However it is recommended co-authorship be formed more heterogeneously instead of a few researches centrally dominate co-authorship. Various researchers should continually conduct research for good research performances.

• Journal of the Korean Society for Library and Information Science
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• v.27
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• pp.215-228
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• 1994

This study is to analyze the background and circumstances of the bibliographical description method appearing in the Hong-ssi Tok-so-rok, or an annotated classified bibliography of Korean and Chinese books edited for the Hongs and their clan. The conclusions are as follows. Each entries of the bibliography are entered under titles, and generally followed by bibliographic elements of volumes, written age, author's name, functional word of authorship, and annotation. The written age is stated by the dynasty name for the first authors within each classes. However some anonymous works and government compiled works are recorded the king's shrine name or the reign title. Entries of the bibliography are arranged by the chronological order in each classes. The writer's name is generally described by 'surname + given name'. However it is sometimes also recorded in the one of the following forms; Appellation (hao, 호) or posthumous title + surname + given name. Sumame + appellation or posthumous title + given name. Appellation ( (hao, 호) or posthumous title + sumame + Sonsaeng (선행) + given name. Sumame + government position title + given name. Appellation (hao, 호) + surname + cha(자, master). surname + ssi(씨). ect. Married women's names are stated by her husband's surname followed by the Chinese character 부 or 절부 which signifies wife or virtuous women, and then her given name. The works written or compiled by King's order (명찬서) are generally described in the form of 명제신+ functional word of authorship. Names of government agencies are occasionally stated as the authors' for the government publications or government compiled works. The functional words of authorship are described in the phrase of 소작야, 소편야 instead of 저, 찬, ect. It is more noticeable that in the case of the collections of individual writers' works the wording of 지문야, 지시야 is written after the name of the author. More complicated descriptive forms are seen in the entries of works for the shared authorship and mixed responsibility. Two or more than two monographic works of the same author classed in the same class are annotated all together.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.203-219
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• 2020

The primary purpose of this study is to identify spatial distribution patterns of co-authoring activities in Korean cadastral science. The analysis showed that a small number of researchers played an essential role in the Korean cadastral co-authorship network. In particular, some authors not only had a significant influence on other nodes in the network but also served as intermediaries between researchers. Moreover, the distance between researchers influenced co-authorship decisions to a limited extent. This study differs considerably from previous studies in that it used spatial analysis techniques to identify spatial distribution patterns of co-authoring activities. However, this research is limited in that it applied only 2019 data to determine the spatial distribution pattern of co-authoring activities. We can overcome this limitation if we analyze the spatial distribution patterns of co-authoring activities using multi-year data in future studies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.6
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• pp.1013-1021
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• 2020

Malware Authorship Attribution is a research field for identifying malware by comparing the author characteristics of unknown malware with the characteristics of known malware authors. The authorship attribution method using binaries has the advantage that it is easy to collect and analyze targeted malicious codes, but the scope of using features is limited compared to the method using source code. This limitation has the disadvantage that accuracy decreases for a large number of authors. This study proposes a method of 'Defining semantic features from binaries' and 'Defining allowable ranges for redundant features using the concept of survival network' to complement the limitations in the identification of binary authors. The proposed method defines Opcode-based graph features from binary information, and defines the allowable range for selecting unique features for each author using the concept of a survival network. Through this, it was possible to define the feature definition and feature selection method for each author as a single technology, and through the experiment, it was confirmed that it was possible to derive the same level of accuracy as the source code-based analysis with an improvement of 5.0% accuracy compared to the previous study.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.20 no.3
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• pp.209-218
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• 2009

This study analyzed the authorship tendency of the authors in the specific organizations. The SCI articles of the authors in H medical center, from 2000 to 2008, were extracted and indexed by the authors. The authorship tendency was analyzed on transience and continuance. As results of analysis, authorship tendency showed continuing tendency not transient tendency. Specifically, the publication rate by new authors was high as the average 39.17% but the publication rate by pre-existence authors, which consisted of the publication rate(16.83%) of reclosing authors and publication rate (44%) of the series author, was relatively higher as the average 60.83%. Also, the extinction author rate of new authors was relatively low as the average 28.2%. the non-flexible publication probability by the author in the specific year was very high as the average 76%. As a result, this study would be used as basic data for the research result management of the organization.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.53-63
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• 2023

The utilization of department information in bibliometric analysis using scientific and technological literature is highly advantageous. In this paper, the department information dataset was built through the screening, data refinement, and classification processing of authors' department type belonging to university institutions appearing in academic journals in the field of science and technology published in Korea, and the automatic classification model based on deep learning was developed using the department information dataset as learning data and verification data. In addition, we analyzed the co-authorship structure and network in the field of computer science using the department information dataset and affiliation information of authors from domestic academic journals. The research resulted in a 98.6% accuracy rate for the automatic classification model using Korean department information. Moreover, the co-authorship patterns of Korean researchers in the computer science and engineering field, along with the characteristics and centralities of the co-author network based on institution type, region, institution, and department type, were identified in detail and visually presented on a map.