• 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.

• Tunnel and Underground Space
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• v.10 no.4
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• pp.506-515
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• 2000

A lot of underground construction projects have been conducted by economical, social and military purposes in Korea for the last three decades. As a result, magnificent amount of data were obtained from geological site investigations, laboratory and field tests, design and field monitoring. But up to now, these valuable informations were neither systematically stored nor utilized efficiently resulting in a great loss of time and money. In this study, a database system named GeoINFO was developed using Microsoft Access 97 for management of informations which can be obtained from underground construction. The developed database system is especially designed to cover three major types of underground facilities-tunnels, underground storages and rock slopes and has multi-layered tree structures for data input. The system also has a unique indexing system for efficient data search using Visual Basic code.

• Journal of the Korean Society for information Management
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• v.32 no.1
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• pp.227-243
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• 2015

The objective of this research was to quantitatively examine the uses of first person pronouns in academic journal paper abstracts. An approximate total of 144,400 abstracts that comprising of four disciplines (chemistry, computer sciences, social sciences, and medicine) from nine countries (China, Germany, India, Japan, South Korea, France, Spain, United Kingdom, and U.S.) were quantitatively examined. By exploring the use of first person pronoun in abstracts, this paper examined the current practices among academics in the world. The results indicate the norms of each author's country and the norms of each discipline. Furthermore, the frequency-count result of this study contradicted viewpoints of academics who disapprove the use of personal person expressions in abstracts. An implication of this study is that there is a need for academics to acknowledge the uses of first person pronoun in the real world before forming personal opinions regarding the first person pronoun.

• The Journal of the Korea Contents Association
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• v.16 no.6
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• pp.205-214
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• 2016

As a large amount of graph-structured data is widely used in various applications such as social networks, semantic web, and bio-informatics, keyword-based search over graph data has been getting a lot of attention. In this paper, we propose an efficient method for keyword search over graph data to find a set of top-k answers that are relevant as well as non-redundant in structure. We define a non-redundant answer structure for a keyword query and a relevance measure for the answer. We suggest a new indexing scheme on the relevant paths between nodes and keyword terms in the graph, and also propose a query processing algorithm to find top-k non-redundant answers efficiently by exploiting the pre-calculated indexes. We present effectiveness and efficiency of the proposed approach compared to the previous method by conducting an experiment using a real dataset.

• Journal of Environmental Science International
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• v.26 no.2
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• pp.133-146
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• 2017

This study aimed to develop strategies to re-establish the Park Nature Conservation Area in Bukhansan National Park, reflecting landscape ecological value by using the zonation program Marxan with Zones. Planning unit was set by watershed, and the basic data were mapped, considering topographical and ecological values. Mapped indicators were analyzed with the application framework of Marxan with Zones by indexing some indicators. The zones divided into Park Nature Conservation Area (Zone A), Park Nature Environment Area I(Zone B) which is reflected on the concept of Potential Park Nature Conservation Area and Park Nature Environment Area II(Zone C). The best solution for each of the scenarios was fixed through the sensitiveness analysis. From these, the final solution was selected considering five criteria including area ratio of conservation area and grouping. Lastly, the final solution was verified in the overlapped analysis with recent zonation. According to the results, the number of watersheds was 77, with an average area of $1,007,481m^2$. In terms of basic mapping and indexation, the slope index and number of landscape resources for topographical property were average 0.22 and 38 places, respectively. Biotope index was average 0.69 and legally protected species was 14 species, reflecting ecological values. As the social and economic indicators, trail index was average 0.04, and the number of tour and management facilities was 43 places. Through the framework of Marxan with Zones, the best solution for scenario 1 which was set by the highest conservation criteria was selected as the final solution, and the area ratio of Park Nature Conservation Area and grouping was excellent. As the result of overlapped analysis, suggested zonation of the Park Nature Conservation was better than the recent zonation in the area raito (28.3%), biotope grade I(15.4%) and the distribution points (10 places) of legally protected species with verification of proper distribution of conservation features according to the zone.

• Journal of Environmental Impact Assessment
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• v.25 no.6
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• pp.402-413
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• 2016

Marine oil spill accidents are occurring continuously due to the marine transportation of the oil. While building a preventive system for oil spill is uttermost necessary, we also need to have a systematic response system to handle the oil spills that inevitably occur. So far, studies have focused on the environmentally sensitive resources affected by oil spills. However, there is a need to conduct research to evaluate the damage to the socially and economically sensitive resources that make up the life of local residents. This study represents the process of building an analytical framework for the assessment of socioeconomic resources affected by marine oil spills. While it is important to provide a scheme for identification and indexation of socially and economically sensitive resources that is compatible with Korea's situations, using existing data for identifying socio-economically sensitive resources might also be meaningful. However, to allow accurate analysis for better evaluation, we need to select more applicable data among the various indicators. In this research, we have reviewed many existing case studies of sensitive resources, studies of the variables that have been used for indexing sensitive resources, and various factors considered in SIA (Social Impact Assessment). Based on the findings, we classify socio-economically sensitive resources into marine products acquisition, population, land usage, administrative area, and cultural heritage and tourist region.

• Anxiety and mood
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• v.11 no.2
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• pp.91-105
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• 2015

Objectives : After disaster, some people develop posttraumatic stress sequelae such as posttraumatic stress disorder (PTSD), major depression, substance use disorders, and suicide. To date, numerous screening and assessment tools for behavioral health issues including mental health problems, psychosocial maladjustment and status of recovery after disaster have been developed. In this condition, one of important topics is to choose instruments that can quickly and accurately measure the issues. Methods : This article reviewed several self-reported scales in adults for disaster behavioral health, which were searched using academic search engines like PubMed, Scopus, KoreaMed and KISS from the earliest available date of indexing through January 31, 2015. Results : More than 40 eligible instruments evaluating the disaster behavioral health issues containing posttraumatic stress sequelae, psychological and social resources, non-disaster stress, and general functions were presented in terms of availability, effectiveness, and expeditiousness. Also, we introduced basic frame aiming on practical usage, which includes standard version and brief version of the instruments for disaster behavioral health. Conclusion : We suggest the accessibility and the applicability of assessment instruments for disaster behavioral health. The systemic review of this article will provide further directions for them.

• Korean Journal of Psychosomatic Medicine
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• v.24 no.1
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• pp.43-53
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• 2016

Objectives : Somatic symptoms after the exposure of psychological trauma frequently developed. However, the somatic symptoms are not covered under the diagnostic criteria of posttraumatic stress disorder(PTSD) in detail, although they are often associated with social and occupational functioning and patient-doctor relationships. The aim of this article is to highlight the potential mechanisms, the common manifestations, and the treatment of the somatic symptoms. Methods : This article studied the somatic symptoms searched using academic search engines like PubMed, Scopus, Google Scholar, KoreaMed and KISS from the earliest available date of indexing to March 31, 2016. Results : The mechanism of somatic symptoms after the exposure was described as psychological and physiological aspects. Psychological mechanism consisted of psychodynamic theory, cognitive behavioral theory, and others. Physiological mechanism involved changes in neuroendocrine and immune system, autonomic nervous system and central nervous system. Somatization associated with psychological trauma manifested various health conditions on head and neck, chest, abdominal, musculoskeletal, and dermatological and immune system. Few studies described the standardization of treatment for the somatic symptoms. Conclusions : Clinicians and disaster behavioral health providers should think of the accompanying somatic symptoms during intervention of psychological trauma and PTSD. Further studies are needed on the somatic symptoms seen in psychological trauma and PTSD.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.5
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• pp.51-62
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• 2012

Geumho-dong, Seoul, a redeveloped residential area, is located in the foothills of Mt. Eungbong. The geographical undulation, the composition of a large apartment complex, and the partial implementation of the redevelopment project have caused the severe physical and social disconnections in this area. In order to recover functioning in the disconnected community, this study pays attention to the regeneration of the open spaces as an everyday place and in the form a network system among those open spaces. Various types of the open spaces are classified into points or faces, 'bases' and linear 'paths' analyze the network status. More than half of the open space have connecting-distance of 500m or more. Furthermore, many areas are not even included in the service-area of the open spaces. Analysis of the connectivity and integration value using the axial map has carried out to check weak linkages and to choose the sections where additional bases are required. In addition, to improve the quality of the bases and the paths, a field investigation is conducted and problems are diagnosed. The network planning of the open spaces in Geumho-dong is established, ensuring the quality and quantity of bases and paths. The plan includes the construction of an additional major base in the central area and six secondary bases in other parts, and comes up with ways to improve the environment of underdeveloped secondary bases. In the neighborhood parks at Mt. Daehyun areas, the major path are added, and the environment of the paths is improved in certain areas. Because of the network planning, the connecting-distances between bases are reduced significantly, the connectivity and integration value of the area are increased, and the service areas of the open spaces cover the whole area properly. Although this study has some limitations such as the needs for the legal and institutional supports and difficulties of a quantitative indexing process, its significance lies in the suggestion of a more reasonable and practical plan for the overall network system by defining complex types of open spaces simply and clearly and by examining the organic relationships quantitatively and qualitatively.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.