• KIISE Transactions on Computing Practices
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• v.21 no.8
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• pp.543-548
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• 2015

Recently, volume of data has been growing dramatically along with the growth of social media and digital devices. However, the existing disk-based distributed file systems have limits to their performance of data processing or data access, due to I/O processing costs and bottlenecks. To solve this problem, the caching technique is being used to manage data in the memory. In this paper, we propose a cache management scheme to handle load balancing in a distributed memory environment. The proposed scheme distributes the data according to the memory size, n distributed environments with different memory sizes. If overloaded nodes occur, it redistributes the the access time of the caching data. In order to show the superiority of the proposed scheme, we compare it with an existing distributed cache management scheme through performance evaluation.

• KIISE Transactions on Computing Practices
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• v.22 no.8
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• pp.357-362
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• 2016

A social network or bio network is one of the complex networks that are formed by connecting specific relationships between interacting objects. Usually, these networks consist of community structures. Automatically detecting the structures is an important technique to understand and control the interaction objects. However, the topologies and structures of the networks change by interactions of the objects, with respect to time. Conventional techniques for finding the community structure have a high computational complexity. Additionally, the methods inefficiently deal with repeated computation concerning graph operation. In this paper, we propose an incremental technique for detecting interaction-based communities in dynamic networks. The proposed technique is able to efficiently find the communities, since there is an awareness of changed objects from the previous network, and it can incrementally reuse the previous community structure.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.1
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• pp.359-380
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• 2018

In the digital society where ICT technology is highly developed, digital literacy is an essential competence for working and living. Developed countries around the world have been working hard to solve the digital divide and improve digital literacy. In this paper, we investigated and analyzed the case of US public libraries for improvement of digital literacy of adults including the older people. To do this, we analyzed the educational program type of digital literacy, education method, and the contents of the program, focusing on the best practices libraries of the program. Many of the educational programs still related to basic computer and Internet technologies, and training programs on Micro Office, e-mail, social media, and smartphone and tablet computing were also high. The most frequent and daily training method was informal point of use, and the content and level of education appeared to be very diverse. For digital literacy training, the librarians of the public library considered librarians' digital competence and retraining to be the most important, and the library facility and the latest equipment to be suitable for the operation of the digital literacy education program.

• Journal of Internet Computing and Services
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• v.11 no.1
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• pp.85-102
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• 2010

In this paper, we propose a novel method of analyzing video and representing the relationship among characters based on their contexts in the video sequences, namely Character-Net. As a huge amount of video contents is generated even in a single day, the searching and summarizing technologies of the contents have also been issued. Thereby, a number of researches have been proposed related to extracting semantic information of video or scenes. Generally stories of video, such as TV serial or commercial movies, are made progress with characters. Accordingly, the relationship between the characters and their contexts should be identified to summarize video. To deal with these issues, we propose Character-Net supporting the extraction of major characters in video. We first identify characters appeared in a group of video shots and subsequently extract the speaker and listeners in the shots. Finally, the characters are represented by a form of a network with graphs presenting the relationship among them. We present empirical experiments to demonstrate Character-Net and evaluate performance of extracting major characters.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.11
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• pp.841-845
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• 2009

The independent cascade model has been widely used to analyze information diffusion in the blog world. In this paper, we propose a new method to construct a blog network for applying the independent cascade model to analyzing of information diffusion in a blog world. To construct a blog network, the proposed method establishes the edge between two users and calculates diffusion probabilities between them by analyzing the activities happened between two users. To calculate diffusion probabilities, the method exploits the ratio of the number of documents actually diffused to a specific user to that of documents written for the purpose of being diffused to other blogs. The experimental result using a real world blog data demonstrates that our method reflects actual information diffusion in a blog world better than existing ones.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.2
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• pp.33-40
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• 2016

Due to the growth of social network systems (SNS), big data are realized and Hadoop was developed as a distributed platform for analyzing big data. Enterprises analyze data containing users' sensitive information by using Hadoop and utilize them for marketing. Therefore, researches on data encryption have been done to protect the leakage of sensitive data stored in Hadoop. However, the existing researches support only the AES encryption algorithm, the international standard of data encryption. Meanwhile, Korean government choose ARIA algorithm as a standard data encryption one. In this paper, we propose a HDFS data encryption scheme using ARIA algorithms on Hadoop. First, the proposed scheme provide a HDFS block splitting component which performs ARIA encryption and decryption under the distributed computing environment of Hadoop. Second, the proposed scheme also provide a variable-length data processing component which performs encryption and decryption by adding dummy data, in case when the last block of data does not contains 128 bit data. Finally, we show from performance analysis that our proposed scheme can be effectively used for both text string processing applications and science data analysis applications.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.35-45
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• 2021

The purpose of this study is to understand the characteristics and trends of active senior. As the baby boom generation become the age of the elderly, they are more active than senior. These seniors are called active seniors, a new consumer group. Many countries and companies are also interested in providing relevant policies and services, but there is lack of researches on active senior trends. This study collects the 8,740 posts related to active seniors on social media from January 1st, 2018 to June 31st, 2021, and conducted keyword frequency analysis, TF-IDF analysis and LDA topic modeling. Through LDA topic modeling, topics are classified into 10 categories: lifestyle, benefits, shopping, government business, government education, health, society and economy, care industry, silver housing, leisure. The results of this study can be utilized as fundamental data to help understand the academic and industrial aspects of active senior.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.93-100
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• 2019

Recently, in various business fields, companies are concentrating on providing chatbot services to various environments by adding artificial intelligence to existing messenger platforms. Organizations in the field of job placement also require chatbot services to improve the quality of employment counseling services and to solve the problem of agent management. A text-based general chatbot classifies input user sentences into learned sentences and provides appropriate answers to users. Recently, user sentences inputted to chatbots are inputted as short texts due to the activation of social network services. Therefore, performance improvement of short text classification can contribute to improvement of chatbot service performance. In this paper, we propose T-EBOW (Translation-Extended Bag Of Words), which is a method to add translation information as well as concept information of existing researches in order to strengthen the short text classification for employment chatbot. The performance evaluation results of the T-EBOW applied to the machine learning classification model are superior to those of the conventional method.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.79-86
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• 2021

As the usefulness of big data analysis has been drawing attention, many studies in the business research area begin to use big data to predict firm performance. Previous studies mainly rely on data outside of the firm through news articles and social media platforms. The voices within the firm in the form of employee satisfaction or evaluation of the strength and weakness of the firm can potentially affect firm value. However, there is insufficient evidence that online employee reviews are valid to predict firm value because the data is relatively difficult to obtain. To fill this gap, from 2014 to 2019, we employed 97,216 reviews collected by JobPlanet, an online firm review website in Korea, and developed a machine learning-based predictive model. Among the proposed models, the LSTM-based model showed the highest accuracy at 73.2%, and the MAE showed the lowest error at 0.359. We expect that this study can be a useful case in the field of firm value prediction on domestic companies.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.57-65
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• 2019

Creative works such as webtoon and web novel are part of property rights. However, illegal copies of them are distributed on the internet easily, which raises social issues in today's society. In order to tackle these problems, this paper proposes and presents a blockchain based copyright management system that ensures forgery prevention, robust security features, improving trading performance, cost-effective, and enhanced visibility. The system allows a user to register creative works formally just the same as before registration and also to register simple creative ideas just anytime. In the latter case, if an idea or a thought flashes across through somebody's mind, he or she can register it to the system immediately without formal registration process and afterward, can utilize a way to prove its originality through the system. Regarding large size images and video files of creative works, the system reduces data size and storage volume sharply to be processed by network entities by storing original creative works separately and including only the hash result of creative works to the transactions.