• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.9
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• pp.12-20
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• 2016

With the enhancements in existing major industries, cloud computing-based converging services have been created, as well as value-added industries. A variety of converging services are now provided, from personalized services up to industrial services. In Korea, they have become the driving force behind existing industries throughout the whole economy, but mainly in finance, mobile systems, social computing, and home services, based on cloud services. However, not only denial of service (DOS) and distributed DOS (DDOS) attacks have occurred, but also attack techniques targeting core data in storage servers. Even security threats that are hardly detected, such as multiple attacks on a certain target, APT, and backdoor penetration have also occurred. To supplement defenses against these, in this article, a protocol for authority management is designed to provide users with safe storage services. This protocol was studied in cases of integration between a cloud environment and big data-based technology, security threats, and their requirements. Also studied were amalgamation examples and their requirements in technology-based cloud environments and big data. With the protocol suggested, based on this, security was analyzed for attack techniques that occur in the existing cloud environment, as well as big data-based techniques, in order to find improvements in session key development of approximately 55%.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.159-172
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• 2020

Social networking services (SNS) are developing significantly with the Internet and smartphones. It's a friendly social media, but if you think deeply about it, you'll find that it has a variety of faces. It is a communication tool between users, a medium for delivering information, an infrastructure for providing applications, and a community where people with common interests gather. In recent years, business tools, shopping and payment methods are also being swallowed. The influence of the spread of SNS on the real world is also expanding, and the work being dealt with from a sociological perspective is also increasing. Also, if you pay attention to the technical aspects of SNS, it is composed of various technical elements, such as infrastructure that handles large-scale access, user interface that supports comfortable use, and big data analysis to understand people's behavior more deeply. However, I usually use it as usual. However, if you look through SNS, you can see that the situation is surprisingly profound and multifaceted. This study began by looking at the history and current status of SNS and attempted to find its status through comparison with other media. From the point of view of relationship with society, it can be a risk and legal issue when using SNS, such as crimes using bad social media or social media. It is also necessary to comment on the activities on SNS or the guidelines established by the operators. Therefore, various legal issues on SNS will be discussed. Also, as an example of using SNS, I will introduce an example of using SNS in disaster response. From a more technical point of view, you will receive commentary on SNS's network-based technology and SNS's information use, and these articles will help you understand and use SNS safely and help you further utilize or develop SNS.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.193-215
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• 2016

In recent years, the proliferation of diverse social networking services has led users to use many mediums simultaneously depending on their individual purpose and taste. Besides, while collecting information about particular themes, they usually employ various mediums such as social networking services, Internet news, and blogs. However, in terms of management, each document circulated through diverse mediums is placed in different categories on the basis of each source's policy and standards, hindering any attempt to conduct research on a specific category across different kinds of sources. For example, documents containing content on "Application for a foreign travel" can be classified into "Information Technology," "Travel," or "Life and Culture" according to the peculiar standard of each source. Likewise, with different viewpoints of definition and levels of specification for each source, similar categories can be named and structured differently in accordance with each source. To overcome these limitations, this study proposes a plan for conducting category mapping between different sources with various mediums while maintaining the existing category system of the medium as it is. Specifically, by re-classifying individual documents from the viewpoint of diverse sources and storing the result of such a classification as extra attributes, this study proposes a logical layer by which users can search for a specific document from multiple heterogeneous sources with different category names as if they belong to the same source. Besides, by collecting 6,000 articles of news from two Internet news portals, experiments were conducted to compare accuracy among sources, supervised learning and semi-supervised learning, and homogeneous and heterogeneous learning data. It is particularly interesting that in some categories, classifying accuracy of semi-supervised learning using heterogeneous learning data proved to be higher than that of supervised learning and semi-supervised learning, which used homogeneous learning data. This study has the following significances. First, it proposes a logical plan for establishing a system to integrate and manage all the heterogeneous mediums in different classifying systems while maintaining the existing physical classifying system as it is. This study's results particularly exhibit very different classifying accuracies in accordance with the heterogeneity of learning data; this is expected to spur further studies for enhancing the performance of the proposed methodology through the analysis of characteristics by category. In addition, with an increasing demand for search, collection, and analysis of documents from diverse mediums, the scope of the Internet search is not restricted to one medium. However, since each medium has a different categorical structure and name, it is actually very difficult to search for a specific category insofar as encompassing heterogeneous mediums. The proposed methodology is also significant for presenting a plan that enquires into all the documents regarding the standards of the relevant sites' categorical classification when the users select the desired site, while maintaining the existing site's characteristics and structure as it is. This study's proposed methodology needs to be further complemented in the following aspects. First, though only an indirect comparison and evaluation was made on the performance of this proposed methodology, future studies would need to conduct more direct tests on its accuracy. That is, after re-classifying documents of the object source on the basis of the categorical system of the existing source, the extent to which the classification was accurate needs to be verified through evaluation by actual users. In addition, the accuracy in classification needs to be increased by making the methodology more sophisticated. Furthermore, an understanding is required that the characteristics of some categories that showed a rather higher classifying accuracy of heterogeneous semi-supervised learning than that of supervised learning might assist in obtaining heterogeneous documents from diverse mediums and seeking plans that enhance the accuracy of document classification through its usage.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.25-41
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• 2014

Recently, the number of social media users has increased rapidly because of the prevalence of smart devices. As a result, the amount of real-time data has been increasing exponentially, which, in turn, is generating more interest in using such data to create added value. For instance, several attempts are being made to analyze the relevant search keywords that are frequently used on new portal sites and the words that are regularly mentioned on various social media in order to identify social issues. The technique of "topic analysis" is employed in order to identify topics and themes from a large amount of text documents. As one of the most prevalent applications of topic analysis, the technique of issue tracking investigates changes in the social issues that are identified through topic analysis. Currently, traditional issue tracking is conducted by identifying the main topics of documents that cover an entire period at the same time and analyzing the occurrence of each topic by the period of occurrence. However, this traditional issue tracking approach has two limitations. First, when a new period is included, topic analysis must be repeated for all the documents of the entire period, rather than being conducted only on the new documents of the added period. This creates practical limitations in the form of significant time and cost burdens. Therefore, this traditional approach is difficult to apply in most applications that need to perform an analysis on the additional period. Second, the issue is not only generated and terminated constantly, but also one issue can sometimes be distributed into several issues or multiple issues can be integrated into one single issue. In other words, each issue is characterized by a life cycle that consists of the stages of creation, transition (merging and segmentation), and termination. The existing issue tracking methods do not address the connection and effect relationship between these issues. The purpose of this study is to overcome the two limitations of the existing issue tracking method, one being the limitation regarding the analysis method and the other being the limitation involving the lack of consideration of the changeability of the issues. Let us assume that we perform multiple topic analysis for each multiple period. Then it is essential to map issues of different periods in order to trace trend of issues. However, it is not easy to discover connection between issues of different periods because the issues derived for each period mutually contain heterogeneity. In this study, to overcome these limitations without having to analyze the entire period's documents simultaneously, the analysis can be performed independently for each period. In addition, we performed issue mapping to link the identified issues of each period. An integrated approach on each details period was presented, and the issue flow of the entire integrated period was depicted in this study. Thus, as the entire process of the issue life cycle, including the stages of creation, transition (merging and segmentation), and extinction, is identified and examined systematically, the changeability of the issues was analyzed in this study. The proposed methodology is highly efficient in terms of time and cost, as it sufficiently considered the changeability of the issues. Further, the results of this study can be used to adapt the methodology to a practical situation. By applying the proposed methodology to actual Internet news, the potential practical applications of the proposed methodology are analyzed. Consequently, the proposed methodology was able to extend the period of the analysis and it could follow the course of progress of each issue's life cycle. Further, this methodology can facilitate a clearer understanding of complex social phenomena using topic analysis.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.4
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• pp.64-73
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• 2021

The purpose of this study is to present a method to assess the landscape aesthetic value of Bukhansan National Park using geotagged images that have been shared on social media sites. The method presented in this study consisted mainly of collecting geotagged image data, identifying landscape images, and analyzing the cumulative visibility by applying a target probability index. Ramblr is an application that supports outdoor activities with many users in Korea, from which a total of 110,954 geotagged images for Bukhansan National Park were collected and used to assess the landscape aesthetics. The collected geotagged images were interpreted using the Google Vision API, and were subsequently were divided into 11 landscape image types and 9 non-landscape image types through cluster analysis. As a result of analyzing the landscape types of Bukhansan National Park based on the extracted landscape images, landscape types related to topographical characteristics, such as peaks and mountain ranges, accounted for the largest portion, and forest landscapes, foliage landscapes, and waterscapes were also commonly found as major landscape types. In the derived landscape aesthetic value map, the higher the elevation and slope, the higher the overall landscape aesthetic value, according to the proportion and characteristics of these major landscape types. However, high landscape aesthetic values were also confirmed in some areas of lowlands with gentle slopes. In addition, the Bukhansan area was evaluated to have higher landscape aesthetics than the Dobongsan area. Despite the high elevation and slope, the Dobongsan area had a relatively low landscape aesthetic value. This shows that the aesthetic value of the landscape is strongly related not only to the physical environment but also to the recreational activities of visitors who are viewing the scenery. In this way, the landscape aesthetics assessment using the cumulative visibility of geotagged images is expected to be useful for planning and managing the landscape of Bukhansan National Park in the future, through allowing the geographical understanding of the landscape values based on people's perceptions and the identification of the regional deviations.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.5
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• pp.69-79
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• 2022

This study aims to assess the current understanding of the landscape of wind power facilities as renewable energy sources that supply sightseeing, tourism, and other opportunities. Therefore, social media data related to the landscape of wind power facilities experienced by visitors from different regions was analyzed. The analysis results showed that the common characteristics of the landscape of wind power facilities are based on the scale of wind power facilities, the distance between overlook points of wind power facilities, the visual openness of the wind power facilities from the overlook points, and the terrain where the wind power facilities are located. In addition, the preference for wind power facilities is higher in places where the shape of wind power facilities and the surrounding landscape can be clearly seen- flat ground or the sea are considered better landscapes. Negative keywords about the landscape appear on Gade Mountain in Taibai, Meifeng Mountain in Taibai, Taiqi Mountain, and Gyeongju Wind Power Generation Facilities on Gyeongshang Road in Gangwon. The keyword 'negation' occurs when looking at wind power facilities at close range. Because of the high angle of the view, viewers can feel overwhelmed seeing the size of the facility and the ridge simultaneously, feeling psychological pressure. On the contrary, positive landscape adjectives are obtained from wind power facilities on flat ground or the sea. Visitors think that the visual volume of the landscape is fully ensured on flat ground or the sea, and it is a symbolic element that can represent the site. This study analyzes landscape awareness based on the opinions of visitors who have experienced wind power facilities. However, wind power facilities are built in different areas. Therefore, landscape characteristics are different, and there are many variables, such as viewpoints and observers, so the research results are difficult to popularize and have limitations. In recent years, landscape damage due to the construction of wind power facilities has become a hot issue, and the domestic methods of landscape evaluation of wind power facilities are unsatisfactory. Therefore, when evaluating the landscape of wind power facilities, the scale of wind power facilities, the inherent natural characteristics of the area where wind power facilities are set up, and the distance between wind power facilities and overlook points are important elements to consider. In addition, wind power facilities are set in the natural environment, which needs to be protected. Therefore, from the landscape perspective, it is necessary to study the landscape of wind power facilities and the surrounding environment.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.95-110
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• 2013

Recently, the amount of unstructured data being generated through a variety of social media has been increasing rapidly, resulting in the increasing need to collect, store, search for, analyze, and visualize this data. This kind of data cannot be handled appropriately by using the traditional methodologies usually used for analyzing structured data because of its vast volume and unstructured nature. In this situation, many attempts are being made to analyze unstructured data such as text files and log files through various commercial or noncommercial analytical tools. Among the various contemporary issues dealt with in the literature of unstructured text data analysis, the concepts and techniques of opinion mining have been attracting much attention from pioneer researchers and business practitioners. Opinion mining or sentiment analysis refers to a series of processes that analyze participants' opinions, sentiments, evaluations, attitudes, and emotions about selected products, services, organizations, social issues, and so on. In other words, many attempts based on various opinion mining techniques are being made to resolve complicated issues that could not have otherwise been solved by existing traditional approaches. One of the most representative attempts using the opinion mining technique may be the recent research that proposed an intelligent model for predicting the direction of the stock index. This model works mainly on the basis of opinions extracted from an overwhelming number of economic news repots. News content published on various media is obviously a traditional example of unstructured text data. Every day, a large volume of new content is created, digitalized, and subsequently distributed to us via online or offline channels. Many studies have revealed that we make better decisions on political, economic, and social issues by analyzing news and other related information. In this sense, we expect to predict the fluctuation of stock markets partly by analyzing the relationship between economic news reports and the pattern of stock prices. So far, in the literature on opinion mining, most studies including ours have utilized a sentiment dictionary to elicit sentiment polarity or sentiment value from a large number of documents. A sentiment dictionary consists of pairs of selected words and their sentiment values. Sentiment classifiers refer to the dictionary to formulate the sentiment polarity of words, sentences in a document, and the whole document. However, most traditional approaches have common limitations in that they do not consider the flexibility of sentiment polarity, that is, the sentiment polarity or sentiment value of a word is fixed and cannot be changed in a traditional sentiment dictionary. In the real world, however, the sentiment polarity of a word can vary depending on the time, situation, and purpose of the analysis. It can also be contradictory in nature. The flexibility of sentiment polarity motivated us to conduct this study. In this paper, we have stated that sentiment polarity should be assigned, not merely on the basis of the inherent meaning of a word but on the basis of its ad hoc meaning within a particular context. To implement our idea, we presented an intelligent investment decision-support model based on opinion mining that performs the scrapping and parsing of massive volumes of economic news on the web, tags sentiment words, classifies sentiment polarity of the news, and finally predicts the direction of the next day's stock index. In addition, we applied a domain-specific sentiment dictionary instead of a general purpose one to classify each piece of news as either positive or negative. For the purpose of performance evaluation, we performed intensive experiments and investigated the prediction accuracy of our model. For the experiments to predict the direction of the stock index, we gathered and analyzed 1,072 articles about stock markets published by "M" and "E" media between July 2011 and September 2011.

• Journal of Korea Entertainment Industry Association
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• v.15 no.2
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• pp.123-135
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• 2021

The data processing of this study is focused on keywords related to 'Corona 19 and professional baseball' and 'Corona 19 and professional baseball no spectators', using text mining and social network analysis of textom program to identify problems and view quality. It was used to set the variable of For quantitative analysis, a questionnaire on viewing quality was constructed, and out of 270 survey respondents, 250 questionnaires were used for the final study. As a tool for securing the validity and reliability of the questionnaire, exploratory factor analysis and reliability analysis were conducted, and IPA analysis (importance-satisfaction) was conducted based on the questionnaire that secured validity and reliability, and the results and strategies were presented. As a result of IPA analysis, factors related to the image (image composition, image coloration, image clarity, image enlargement and composition, high-quality image) were found in the first quadrant, and the second quadrant was the game situation (support team game level, support player game level, star). Player discovery, competition with rival teams), game information (match schedule information, player information check, team performance and player performance, game information), interaction (consensus with the supporting team), and some factors appeared. The factors of commentator (baseball-related knowledge, communication ability, pronunciation and voice, use of standard language, introduction of game-related information) and interaction (real-time communication with the front desk, sympathy with viewers, information exchange such as chatting) appeared.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.143-159
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• 2015

Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.4
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• pp.175-196
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• 2022

This study aims to determine the research trends in archival preservation through keyword analysis, understand the current research status, and identify the research topics' changes over time. The degree and betweenness centrality analyses were conducted and visualized on 463 "archival preservation studies" articles published from 2000 to 2021 in various academic journals, using NetMiner 4.0. The collected research papers were divided into three time periods according to when they were published: the first period (2000-2007), the second period (2008-2014), and the third period (2015-2021). The subject keywords for the research papers on archival preservation in Korea that have influence and expandability are as follows. Across all periods, these were "electronic records" and "long-term preservation." In addition, if taken separately per period, the "OAIS reference model" and "electronic records" dominated the first and second periods, respectively, while the "records management standard table" and "long-term preservation" both dominated the third period. A conceptual framework and theory-oriented study for archival preservation, such as "digital preservation," "digitalization," and the "OAIS reference model," dominated the first period. During the second period, more research focused on procedures and practical applications related to conservation activities, such as "electronic record," "appraisal," and "DRAMBORA." In contrast, the majority of the research in the third period was on technical implementation according to the changes in the records management environment, such as "data set," "administrative information system," and "social media."