• Journal of the Korea Society of Computer and Information
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• v.22 no.7
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• pp.55-62
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• 2017

Recently, there has been an increasing need for the sharing of microdata containing information regarding an individual entity. As microdata usually contains sensitive information on an individual, releasing it directly for public use may violate existing privacy requirements. Thus, to avoid the privacy problems that occur through the release of microdata for public use, extensive studies have been conducted in the area of privacy-preserving data publishing (PPDP). The k-anonymity algorithm, which is the most popular method, guarantees that, for each record, there are at least k-1 other records included in the released data that have the same values for a set of quasi-identifier attributes. Given an original table, the corresponding k-anonymous table is obtained by generalizing each record in the table into an indistinguishable group, called the equivalent class, by replacing the specific values of the quasi-identifier attributes with more general values. However, query processing over the anonymized data is a very challenging task, due to generalized attribute values. In particular, the problem becomes more challenging with an equi-join query (which is the most common type of query in data analysis tasks) over k-anonymous tables, since with the generalized attribute values, it is hard to determine whether two records can be joinable. Thus, to address this challenge, in this paper, we develop a novel scheme that is able to effectively perform an equi-join between k-anonymous tables. The experiment results show that, through the proposed method, significant gains in accuracy over using a naive scheme can be achieved.

• Journal of Software Engineering Society
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• v.24 no.3
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• pp.101-110
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• 2011

Web Service which consists of SOAP, WSDL and UDDI is a software system that enables interactions of heterogeneous systems on networks with standardized XML message. Especially, UDDI is a registry for supporting the registration of a service by service publisher and discovery of a service by service requester. The preliminary studies are just about publishing and searching services. It presents the researches about UDDI study for improvement of searching a service and extended UDDI design for improvement of reusability with service components aspects. In this paper, we suggest not only features about publishing and searching services of existing UDDI system but also novel UDDI data structures and API for a reusable service model. In addition, we design and implement an extended UDDI system for publishing and finding the reusable services. Therefore, by using proposed UDDI systems, service developers reduce development costs and time through developing a service application reusing the already implemented services. In addition, it can expect to ensure the quality of services by reusing the proven services.

• Journal of The Korean Society of Integrative Medicine
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• v.8 no.4
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• pp.1-11
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• 2020

Purpose : The purpose of this meta-analysis was to examine the effects of microcurrent on inflammatory musculoskeletal diseases. Methods : Domestic databases (RISS, NDSL, KISS, DBpia, and Kmbase) were searched for studies that conducted clinical trials associated with microcurrent and its impact on inflammatory musculoskeletal diseases. A total of 606 studies published between 2002 and 2019 were identified, with 8 studies satisfying the inclusion data. The studies were classified according to patient, intervention, comparison, and outcome (PICO). The search outcomes were items associated with blood component, pain, and function. The 8 studies that were included in the study were evaluated using R meta-analysis (version 4.0). The quality of 7 randomized control trials was evaluated using Cochrane risk of bias (ROB). The quality of 1 non-randomized control trial was evaluated using risk of bias assessment tool for non-randomized studies (RoBANS). Effect sizes were computed as the corrected standard mean difference (SMD). A random-effect model was used to analyze the effect size because of the high heterogeneity among the studies. Egger's regression test was carried out to analyze the publishing bias. Results : The following factors had a large effect size involving microcurrent on inflammatory musculoskeletal diseases: blood component (Hedges's g=-2.46, 95 % CI=-4.20~-0.73), pain (Hedges's g=3.51, 95 % CI=2.44~4.77), and function (Hedges's g=3.06, 95 % CI: 1.53~4.58). Except for function (t=1.572, p=.191), Egger's regression test showed that the publishing bias had statistically significant differences. Conclusion : This study provides evidence for the effectiveness of microcurrent on inflammatory musculoskeletal diseases in terms of blood component, pain, and function. However, due to the small sample sizes used in the included studies, the results of our study should be interpreted cautiously, especially considering the publishing bias.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.409-434
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• 2023

This study analyzes the authorship of all articles published in four domestic LIS journals over a 20-year period from 2002 to 2021 to examine the current status of scholarly communication through Korean LIS journals and suggest future prospects. To achieve this purpose, the study analyzed the number of co-authors, the proportion of returning authors, the publishing preference index (PPI), the author group change trend, and the researcher attraction index (RAI). The analysis revealed the level of collaborative research in each journal, the degree of formation of related author groups by journal, the inflection point of author group changes, the characteristics of emerging researchers, and the degree of author sharing between journals. Overall, 2015 was found to be an inflection point where the author community of Korean LIS journals changed. The newer generation of researchers showed a slightly different behavior of publishing papers than the older generation, as they mainly conduct collaborative research. These quantitative results could be triangulated with the qualitative interview data of previous studies to further strengthen the development strategy of Korean LIS journals.

• Journal of The Korean Society of Integrative Medicine
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• v.7 no.4
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• pp.119-130
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• 2019

Purpose : The purpose of this study was to investigate the meta-analysis on the effects of action observation training on stroke patients' walking. Methods : Domestic databases (DBpia, KISS, NDSL, and RISS) were searched for studies that conducted randomized controlled trials (RCTs) associated with action observation training in adults after stroke. The search outcomes were items associated with the walking function. The 18 studies that were included in the study were analyzed using R meta-analysis. A random-effect model was used for the analysis of the effect size because of the significant heterogeneity among the studies. Sub-group and meta-regression analysis were also used. Egger's regression test was conducted to analyze the publishing bias. Cumulative meta-analysis and sensitivity analysis were also done to analyze a data error. Results : The mean effect size was 2.77. The sub-group analysis showed a statistical difference in the number of training sessions per week. No statistically significant difference was found in the meta-regression analysis. Publishing bias was found in the data, but the results of the trim-and-fill method showed that such bias did not affect the obtained data. Also, the cumulative meta-analysis and sensitivity analysis showed no data errors. Conclusion : The meta-analysis of the studies that conducted randomized clinical trials revealed that action observation training effectively improved walking of the chronic stroke patients.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.57-68
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• 2017

The Linked Open Data(LOD) cloud is quickly becoming one of the largest collections of interlinked datasets and the de facto standard for publishing, sharing and connecting pieces of data on the Web. Data publishers from diverse domains publish their data using Resource Description Framework(RDF) data model and provide SPARQL endpoints to enable querying their data, which enables creating a global, distributed and interconnected dataspace on the LOD cloud. Although it is possible to extract structured data as query results by using SPARQL, users have very poor in analysis and visualization of RDF data from SPARQL query results. Therefore, to tackle this issue, based on Formal Concept Analysis, we propose a novel approach for analyzing and visualizing useful information from the LOD cloud. The RDF data analysis and visualization technique proposed in this paper can be utilized in the field of semantic web data mining by extracting and analyzing the information and knowledge inherent in LOD and supporting classification and visualization.

• Journal of Information Processing Systems
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• v.20 no.4
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• pp.524-534
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• 2024

The release of relational data containing personal sensitive information poses a significant risk of privacy breaches. To preserve privacy while publishing such data, it is important to implement techniques that ensure protection of sensitive information. One popular technique used for this purpose is data perturbation, which is popularly used for privacy-preserving data release due to its simplicity and efficiency. However, the data perturbation has some limitations that prevent its practical application. As such, it is necessary to propose alternative solutions to overcome these limitations. In this study, we propose a novel approach to preserve privacy in the release of relational data containing personal sensitive information. This approach addresses an intuitive, syntactic privacy criterion for data perturbation and two perturbation methods for relational data release. Through experiments with synthetic and real data, we evaluate the performance of our methods.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.1-16
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• 2023

Synthetic data generation is generally used in performance evaluation and function tests in data-intensive applications, as well as in various areas of data analytics, such as privacy-preserving data publishing (PPDP) and statistical disclosure limit/control. A significant amount of research has been conducted on tools and languages for data generation. However, existing tools and languages have been developed for specific purposes and are unsuitable for other domains. In this article, we propose a regular expression-based data generation language (DGL) for flexible big data generation. To achieve a general-purpose and powerful DGL, we enhanced the standard regular expressions to support the data domain, type/format inference, sequence and random generation, probability distributions, and resource reference. To efficiently implement the proposed language, we propose caching techniques for both the intermediate and database queries. We evaluated the proposed improvement experimentally.

• Knowledge Management Research
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• v.16 no.4
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• pp.157-168
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• 2015

Opening government data has been one of the main goals of nations building their e-government structures. Nonetheless, more than publishing government data for public viewing, the bigger concern right now is promoting the use change to "and proving the usefulness of available public data". In order to do this, governments must be able to, not only publicize data but more so, publish the kind of data usable to infomediaries and developers in order to create new products and services for citizens. This research investigates 30 open data use cases of South Korea as listed in Data.go.kr. This study aims to contribute to a better understanding of open datasets utilization in a technologically-advanced and well-developed nation and hopefully provide some useful insights on how open data is currently being used, how it is opening up new business, and more importantly, how it is contributing to the civic society by providing services to the public.

• Knowledge Management Research
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• v.19 no.3
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• pp.189-223
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• 2018

This paper examined the effect of innovation networks comprising research and development (R&D) collaboration on innovation performance of Korean pharmaceutical firms. As co-assigned patents and co-affiliated publications are common technical outcomes of successful R&D collaboration in the pharmaceutical industry, social network analysis technique was applied for analyzing innovation networks through patent and publication data. Results of Social network analysis indicated that a small set of highly innovative firms in the Korean pharmaceutical industry were actively involved in patenting and publishing. And the analysis of structural equation model found the followings: (1) R&D intensity significantly affected patenting, publication and new drug development, (2) the activity of patenting and publishing was positively related with the innovation performance measured by new drug development, and (3) R&D collaboration in terms of degree centrality of co-patent network played significant moderating roles on the relationships among R&D intensity, patenting, and new drug development. These findings are expected to be helpful to researchers as well as policy-makers to devise innovation-promoting policies in the Korean pharmaceutical industry. Discussions and limitations of the study are provided in the last part.