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Kyoungsoo Bok
Department of SW Convergence Technology, Wonkwang University, Iksandae 460, Iksan 54538, Korea

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Short Biography

Department of SW Convergence Technology, Wonkwang University, Iksandae 460, Iksan, Jeonbuk 54538

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Journal article
Published: 27 August 2021 in Applied Sciences
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Owing to the recent advancements in Internet of Things technology, social media, and mobile devices, real-time stream balancing processing systems are commonly used to process vast amounts of data generated in various media. In this paper, we propose a dynamic task scheduling scheme considering task deadlines and node resources. The proposed scheme performs dynamic scheduling using a heterogeneous cluster consisting of various nodes with different performances. Additionally, the loads of the nodes considering the task deadlines are balanced by different task scheduling based on three defined load types. Based on diverse performance evaluations it is shown that the proposed scheme outperforms the conventional schemes.

ACS Style

Dojin Choi; Hyeonwook Jeon; Jongtae Lim; Kyoungsoo Bok; Jaesoo Yoo. Dynamic Task Scheduling Scheme for Processing Real-Time Stream Data in Storm Environments. Applied Sciences 2021, 11, 7942 .

AMA Style

Dojin Choi, Hyeonwook Jeon, Jongtae Lim, Kyoungsoo Bok, Jaesoo Yoo. Dynamic Task Scheduling Scheme for Processing Real-Time Stream Data in Storm Environments. Applied Sciences. 2021; 11 (17):7942.

Chicago/Turabian Style

Dojin Choi; Hyeonwook Jeon; Jongtae Lim; Kyoungsoo Bok; Jaesoo Yoo. 2021. "Dynamic Task Scheduling Scheme for Processing Real-Time Stream Data in Storm Environments." Applied Sciences 11, no. 17: 7942.

Journal article
Published: 20 August 2021 in Applied Sciences
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In this paper, we propose a method for recommending experts to appropriately answer questions based on social activity analysis on social media. By analyzing various social activities performed on social media, the user’s interests are identified. Through the human relation analysis of the users of a particular interest field and by considering the response speed and answer quality of the user, we determine the influence of a user. An expert group is matched by analyzing the content of queries by a user and using a hierarchical structure of words. For a user question, the accuracy of an expert recommendation is enhanced by incorporating the question content and sublevel words based on the hierarchical structure of words. Various evaluations have demonstrated that the performance of the proposed method is superior to existing methods.

ACS Style

Kyoungsoo Bok; Heesub Song; Dojin Choi; Jongtae Lim; Deukbae Park; Jaesoo Yoo. Expert Recommendation for Answering Questions on Social Media. Applied Sciences 2021, 11, 7681 .

AMA Style

Kyoungsoo Bok, Heesub Song, Dojin Choi, Jongtae Lim, Deukbae Park, Jaesoo Yoo. Expert Recommendation for Answering Questions on Social Media. Applied Sciences. 2021; 11 (16):7681.

Chicago/Turabian Style

Kyoungsoo Bok; Heesub Song; Dojin Choi; Jongtae Lim; Deukbae Park; Jaesoo Yoo. 2021. "Expert Recommendation for Answering Questions on Social Media." Applied Sciences 11, no. 16: 7681.

Journal article
Published: 11 January 2021 in Sensors
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As various types of data are generated on the social Internet of things (SIoT), which combine the Internet of things (IoT) and social networks, the relations of IoT devices should be established for necessary data exchange. In this paper, we propose a user recommendation scheme that facilitates data sharing through an analysis of an interaction between an IoT device and a user in the SIoT. An interrelation between a user and an IoT device as well as an interrelation between users exist simultaneously in the SIoT. Hence, the interaction between users must be analyzed to identify the interest keywords, and the interaction between IoT devices and users to determine the user’s preference of IoT device. Moreover, the proposed scheme calculates the similarity between users based on the IoT device preference based on IoT device usage frequency and interest keywords, which are identified through an analysis between the user and IoT device and that between users. Subsequently, it recommends top-N users who have a high similarity as the users for data sharing. Furthermore, the performance of the proposed scheme is verified through performance evaluation based on the precision, recall, and F-measure.

ACS Style

Kyoungsoo Bok; Yeondong Kim; Dojin Choi; Jaesoo Yoo. User Recommendation for Data Sharing in Social Internet of Things. Sensors 2021, 21, 462 .

AMA Style

Kyoungsoo Bok, Yeondong Kim, Dojin Choi, Jaesoo Yoo. User Recommendation for Data Sharing in Social Internet of Things. Sensors. 2021; 21 (2):462.

Chicago/Turabian Style

Kyoungsoo Bok; Yeondong Kim; Dojin Choi; Jaesoo Yoo. 2021. "User Recommendation for Data Sharing in Social Internet of Things." Sensors 21, no. 2: 462.

Article
Published: 08 January 2021 in The Journal of Supercomputing
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Most researchers establish research directions in their study of new fields by providing expert advice or publishing expert papers. The existing academic search services display papers by field but do not provide experts by field. Therefore, researchers are left to judge experts in each field by analyzing the papers for themselves. In this paper, we design and implement an expert search system based on papers that have been published in the academic societies. The academic expert search system is based on a big data processing system to handle a large amount of data in academic fields. It calculates an expert score using quality and influence factors. The quality factor is calculated based on the citations, impact factor, and recentness of a paper. The influence factor is measured by the sparsity of a field and the degree of contributiveness of an author. The proposed system provides various services such as expert searches, keyword searches, the hot topics, expert relationships, and academic society statistics. By finding experts in a specific field, our system can support researchers’ research activities.

ACS Style

Dojin Choi; Hyeonbyeong Lee; Kyoungsoo Bok; Jaesoo Yoo. Design and implementation of an academic expert system through big data analysis. The Journal of Supercomputing 2021, 77, 7854 -7878.

AMA Style

Dojin Choi, Hyeonbyeong Lee, Kyoungsoo Bok, Jaesoo Yoo. Design and implementation of an academic expert system through big data analysis. The Journal of Supercomputing. 2021; 77 (7):7854-7878.

Chicago/Turabian Style

Dojin Choi; Hyeonbyeong Lee; Kyoungsoo Bok; Jaesoo Yoo. 2021. "Design and implementation of an academic expert system through big data analysis." The Journal of Supercomputing 77, no. 7: 7854-7878.

Journal article
Published: 08 January 2021 in Applied Sciences
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In this paper, we propose a local event detection scheme by analyzing relevant documents in social networks to improve the accuracy of event detection. To detect local events by using geographical data, the proposed scheme embeds them using a geographical data dictionary and generates a weighted keyword graph using social network characteristics. The data left by users in social networks include not only postings but also related documents such as comments and threads. In this way, the proposed scheme detects a local event based on a keyword graph that is constructed through the analysis of the relevant documents. This can improve the accuracy of local event detection by analyzing relevant documents embedded with region-related information using a geographical data dictionary, without requiring users to tag geographic data. In order to verify the superiority of the proposed scheme, we compare it with the existing event detection schemes through various performance evaluations.

ACS Style

Dojin Choi; Soobin Park; Dongho Ham; Hunjin Lim; Kyoungsoo Bok; Jaesoo Yoo. Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks. Applied Sciences 2021, 11, 577 .

AMA Style

Dojin Choi, Soobin Park, Dongho Ham, Hunjin Lim, Kyoungsoo Bok, Jaesoo Yoo. Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks. Applied Sciences. 2021; 11 (2):577.

Chicago/Turabian Style

Dojin Choi; Soobin Park; Dongho Ham; Hunjin Lim; Kyoungsoo Bok; Jaesoo Yoo. 2021. "Local Event Detection Scheme by Analyzing Relevant Documents in Social Networks." Applied Sciences 11, no. 2: 577.

Journal article
Published: 09 August 2020 in Applied Sciences
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Graphs have been utilized in various fields because of the development of social media and mobile devices. Various studies have also been conducted on caching techniques to reduce input and output costs when processing a large amount of graph data. In this paper, we propose a two-level caching scheme that considers the past usage pattern of subgraphs and graph connectivity, which are features of graph topology. The proposed caching is divided into a used cache and a prefetched cache to manage previously used subgraphs and subgraphs that will be used in the future. When the memory is full, a strategy that replaces a subgraph inside the memory with a new subgraph is needed. Subgraphs in the used cache are managed by a time-to-live (TTL) value, and subgraphs with a low TTL value are targeted for replacement. Subgraphs in the prefetched cache are managed by the queue structure. Thus, first-in subgraphs are targeted for replacement as a priority. When a cache hit occurs in the prefetched cache, the subgraphs are migrated and managed in the used cache. As a result of the performance evaluation, the proposed scheme takes into account subgraph usage patterns and graph connectivity, thus improving cache hit rates and data access speeds compared to conventional techniques. The proposed scheme can quickly process and analyze large graph queries in a computing environment with small memory. The proposed scheme can be used to speed up in-memory-based processing in applications where relationships between objects are complex, such as the Internet of Things and social networks.

ACS Style

Kyoungsoo Bok; Seunghun Yoo; Dojin Choi; Jongtae Lim; Jaesoo Yoo. In-Memory Caching for Enhancing Subgraph Accessibility. Applied Sciences 2020, 10, 5507 .

AMA Style

Kyoungsoo Bok, Seunghun Yoo, Dojin Choi, Jongtae Lim, Jaesoo Yoo. In-Memory Caching for Enhancing Subgraph Accessibility. Applied Sciences. 2020; 10 (16):5507.

Chicago/Turabian Style

Kyoungsoo Bok; Seunghun Yoo; Dojin Choi; Jongtae Lim; Jaesoo Yoo. 2020. "In-Memory Caching for Enhancing Subgraph Accessibility." Applied Sciences 10, no. 16: 5507.

Journal article
Published: 28 May 2020 in Electronics
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Since dynamic graph data continuously change over time, it is necessary to manage historical data for accessing a snapshot graph at a specific time. In this paper, we propose a new historical graph management scheme that consists of an intersection snapshot and a delta snapshot to enhance storage utilization and historical graph accessibility. The proposed scheme constantly detects graph changes and calculates a common subgraph ratio between historical graphs over time. If the common subgraph ratio is lower than a threshold value, the intersection snapshot stores the common subgraphs within a time interval. A delta snapshot stores the subgraphs that are not contained in the intersection snapshot. Several delta snapshots are connected to the intersection snapshot to maintain the modified subgraph over time. The efficiency of storage space is improved by managing common subgraphs stored in the intersection snapshot. Furthermore, the intersection and delta snapshots can be connected to search a graph at a specific time. We show the superiority of the proposed scheme through various performance evaluations.

ACS Style

Kyoungsoo Bok; Gihoon Kim; Jongtae Lim; Jaesoo Yoo. Historical Graph Management in Dynamic Environments. Electronics 2020, 9, 895 .

AMA Style

Kyoungsoo Bok, Gihoon Kim, Jongtae Lim, Jaesoo Yoo. Historical Graph Management in Dynamic Environments. Electronics. 2020; 9 (6):895.

Chicago/Turabian Style

Kyoungsoo Bok; Gihoon Kim; Jongtae Lim; Jaesoo Yoo. 2020. "Historical Graph Management in Dynamic Environments." Electronics 9, no. 6: 895.

Journal article
Published: 02 November 2019 in Electronics
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Skyline query-processing techniques considering various properties in peer to peer (P2P)-based services have become a recent topic of research. In this paper, we propose a new skyline query-processing scheme to improve the query-processing performance and accuracy in a mobile P2P service over delay-tolerant networks. The proposed scheme collects data on the query object from neighboring nodes and establishes a local skyline through static properties to reduce query-processing costs. To improve the query accuracy in a non-uniform distribution environment, the query-dissemination range is expanded by enforcing a query-dissemination range expansion. The performance evaluation conducted to verify the superiority of the proposed scheme demonstrates that it has a better performance compared to the existing schemes.

ACS Style

Kyoungsoo Bok; Sunyong Park; Jongtae Lim; Jaesoo Yoo; Bok; Park; Lim; Yoo. Mobile P2P-Based Skyline Query Processing over Delay-Tolerant Networks. Electronics 2019, 8, 1276 .

AMA Style

Kyoungsoo Bok, Sunyong Park, Jongtae Lim, Jaesoo Yoo, Bok, Park, Lim, Yoo. Mobile P2P-Based Skyline Query Processing over Delay-Tolerant Networks. Electronics. 2019; 8 (11):1276.

Chicago/Turabian Style

Kyoungsoo Bok; Sunyong Park; Jongtae Lim; Jaesoo Yoo; Bok; Park; Lim; Yoo. 2019. "Mobile P2P-Based Skyline Query Processing over Delay-Tolerant Networks." Electronics 8, no. 11: 1276.

Journal article
Published: 15 October 2019 in Electronics
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Recently, social network services that express individual opinions and thoughts have been significantly developed. As unreliable information is generated and shared by arbitrary users in social network services, many studies have been conducted to find users who provide reliable and professional information. In this paper, we propose an expert finding scheme to discover users who can answer users’ questions professionally in social network services. We use a dynamic profile to extract the user’s latest interest through an analysis of the user’s recent activity. To improve the accuracy of the expert finding results, we consider the user trust and response quality. We conduct a performance evaluation with the existing schemes through various experiments to verify the superiority of the proposed scheme.

ACS Style

Kyoungsoo Bok; Inbae Jeon; Jongtae Lim; Jaesoo Yoo. Expert Finding Considering Dynamic Profiles and Trust in Social Networks. Electronics 2019, 8, 1165 .

AMA Style

Kyoungsoo Bok, Inbae Jeon, Jongtae Lim, Jaesoo Yoo. Expert Finding Considering Dynamic Profiles and Trust in Social Networks. Electronics. 2019; 8 (10):1165.

Chicago/Turabian Style

Kyoungsoo Bok; Inbae Jeon; Jongtae Lim; Jaesoo Yoo. 2019. "Expert Finding Considering Dynamic Profiles and Trust in Social Networks." Electronics 8, no. 10: 1165.