• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.59-66
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• 2005

The organization of the web is progressively more being used to improve search and analysis of information on the web as a large collection of heterogeneous documents. Most people begin at a Web search engine to find information. but the user's pertinent search results are often greatly diluted by irrelevant data or sometimes appear on target but still mislead the user in an unwanted direction. One of the intentional, sometimes vicious manipulations of Web databases is a intentionally biased web page like Google bombing that is based on the PageRank algorithm. one of many Web structuring techniques. In this thesis, we regard the World Wide Web as a directed labeled graph that Web pages represent nodes and link edges. In the Present work, we define the label of an edge as having a link context and a similarity measure between link context and target page. With this similarity, we can modify the transition matrix of the PageRank algorithm. By suggesting a motivating example, it is explained how our proposed algorithm can filter the Web intentionally biased web Pages effective about $60\%% rather than the conventional PageRank.

• Journal of Environmental Science International
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• v.17 no.6
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• pp.591-599
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• 2008

In order to support the development of wind farms in Jejudo, a wind resource database for Jejudo has been established using a meteor-statistical analysis of KIER(Korea Institute of Energy Research) met-mast measurements and KMA(Korea Meteorological Administration) weather data. The analysis included wind statistics, tower shading, an exposure category classification using satellite images, the effect of atmospheric stability on the wind profile exponent, and a correlation matrix of wind speed to gain an understanding of the meteorological correlation between long-term weather observation stations and short-term met-mast measurements. The wind resource database for Jejudo, is to be provided as an add-on to Google $Earth^{TM}$, which is expected to be utilized as a guideline for the selection of an appropriate reference site for long-term correction in the next wind farm development project.

• The Journal of Korean Academic Society of Nursing Education
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• v.17 no.3
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• pp.395-404
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• 2011

Purpose: The purpose of this paper was to analyze research papers using movies and to introduce a practical instruction in cinema education for nurse educators in Korea. Method: The computerized database of PubMed, Google scholar, NDSL, CINAHL, and PsychINFO were used to generate relevant literature. Sixteen studies were published between 1990 and 2011 and were included in this review. These papers were analyzed using the matrix method suggested by Garrad (2007). Results: The first paper using movies in nursing education was performed in 1995. There were 16 studies on this issue and classified into one qualitative and 15 quantitative research. Because psychiatric mental health nursing was the main course, movies relating to mental illness were mainly considered. Most papers used questionnaires developed by researchers and discussions regarding the course. The key findings in these papers were all positive. Conclusion: The critics and syntheses in these papers emerged into seven overarching merits of cinema education and that lead to conduct cinema education to deepen students' understanding and to evoke empathy, critical thinking, entertainment, and intimacy. In addition, cinema education was safe and economical. This study recommends discovering suitable films and developments in both instruction process and educational evaluation tools.

• Journal of Korean Medicine for Obesity Research
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• v.18 no.2
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• pp.128-143
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• 2018

Objectives: The purpose of this study is to investigate the efficacy and the mechanisms of dietary supplements in cellulite treatment, and then to provide the theoretical and clinical basis for the cellulite treatment in Korean Medicine. Methods: We searched for articles from Korea, China, and English electronic database (Koreanstudies Information Service System [KISS], National Digital Science Library [NDSL], KMbase, Research Information Sharing Service [RISS], Oriental Medicine Advanced Searching Integrated System [OASIS], National Assembly Library, Korean Traditional Knowledge Portal, Google scholar, PubMed, Scopus, China National Knowledge Infrastructure [CNKI]) until April 2018. We chose clinical trial studies by inclusion criteria through titles, abstracts and articles. Results: A total of 10 studies were selected through search. The experimental group had shown more effective cellulite improvement in 90% of studies. Also, improvement of symptoms related with cellulite like pain, edema, heaviness and increase of skin surface temperature were observed in experimental group. In addition, the density of connective tissues of the dermal layer was increased in experimental group. Conclusions: The use of dietary supplements in cellulite treatment is thought to be effective through mechanisms that antioxidant efficacy, microcirculation improvement, interstitial matrix improvement, diuretic effect, and skin metabolic activity effect.

• Korean Journal of Occupational Health Nursing
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• v.28 no.4
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• pp.221-229
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• 2019

Purpose: The aim of this study was to identify core keywords and topic groups of workplace bullying researches in the past 10 years for better understanding research trend. Methods: The study was conducted in four steps: 1) collecting abstracts, 2) extracting and cleaning semantic morphemes, 3) building co-occurrence matrix and 4) analyzing network features and clustering topic groups. Results: 437 articles between 2010 and 2019 were retrieved from 5 databases (RISS, NDSL, Google scholar, DBPIA and Kyobo Scholar). Forty-one abstracts from these articles were extracted, and network analysis was conducted using semantic network module. The most important core keywords were 'turnover', 'intention', 'factor', 'program' and 'nursing'. Four topic groups were identified from Korean databases. Major topics were 'turnover' and 'organization culture'. Conclusion: After reviewing previous research, it has been found that turnover intention has been emphasized. Further research focused on various intervention is needed to relieve workplace bullying in nursing field.

• Asia-Pacific Journal of Business
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• v.11 no.1
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• pp.1-16
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• 2020

Purpose - The purpose of this research is to investigate the determinants of bakery revisit intention. This research selects Paris Baguette as the research context because the market share of Paris Baguette was the highest in Korean bakery market. Design/methodology/approach -This research employed revisit intention as the dependent variable, while this research chooses six attributes to account for revisit intention. Six attributes are price fairness, taste, product variety, accessibility, display, and membership. This research uses survey as the main instrument. For the data collection, online survey using Google survey form was implemented. The survey participants are domestic consumers of Paris Baguette. The number of observation is 245. For the data analysis, this study used frequency analysis, correlation matrix, exploratory factor analysis, reliability analysis, and multiple regression model. There are four control variables, which contains age, gender, visiting frequency, and monthly income. Findings - The results shows that price fairness, taste, product diversity, and accessibility are significant attributes with the positive effect. Among the significant attributes, taste presented the highest magnitude to explain the revisit intention. However, membership and display appeared as non-significant attributes to account for bakery revisit intention. Research implications or Originality - This study provides the bakery managers with the information to design their service and product. This study also contributes to the literature by understanding the consumer behavior more in the domain of bakery service.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.222-230
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• 2023

The purpose of this study is to provide basic data on sports entertainment programs by collecting data on unstructured data generated by Naver and Google for SBS entertainment program 'Women Who Score Goal', which began regular broadcast in June 2021, and analyzing public perceptions through data mining, semantic matrix, and CONCOR analysis. Data collection was conducted using Textom, and 27,911 cases of data accumulated for 16 months from June 16, 2021 to October 15, 2022. For the collected data, 80 key keywords related to 'Kick a Goal' were derived through simple frequency and TF-IDF analysis through data mining. Semantic network analysis was conducted to analyze the relationship between the top 80 keywords analyzed through this process. The centrality was derived through the UCINET 6.0 program using NetDraw of UCINET 6.0, understanding the characteristics of the network, and visualizing the connection relationship between keywords to express it clearly. CONCOR analysis was conducted to derive a cluster of words with similar characteristics based on the semantic network. As a result of the analysis, it was analyzed as a 'program' cluster related to the broadcast content of 'Kick a Goal' and a 'Soccer' cluster, a sports event of 'Kick a Goal'. In addition to the scenes about the game of the cast, it was analyzed as an 'Everyday Life' cluster about training and daily life, and a cluster about 'Broadcast Manipulation' that disappointed viewers with manipulation of the game content.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.3
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• pp.889-896
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• 2015

Matrix metalloproteinase-2 (MMP2) is an endopeptidase, mainly responsible for degradation of extracellular matrix components, which plays an important role in cancer disease. A single nucleotide polymorphism (SNP) at -1306 disrupts a Sp1-type promoter site. The results from the published studies on the association between MMP2 -1306 C>T polymorphism and cancer risk are contradictory and inconclusive. In the present study, a meta-analysis was therefore performed to evaluate the strength of any association between the MMP2 -1306 C>T polymorphism and risk of cancer. We searched all eligible studies published on association between MMP2 -1306 C>T polymorphism and cancer risk in PubMed (Medline), EMBASE and Google Scholar online web databases until December 2013. Genotype distribution data were collected to calculate the pooled odds ratios (ORs) and 95% confidence intervals (95%CIs) to examine the strength of the association. A total of 8,590 cancer cases and 9,601 controls were included from twenty nine eligible case control studies. Overall pooled analysis suggested significantly reduced risk associated with heterozygous genotype (CT vs CC: OR=0.758, 95%CI=0.637 to 0.902, p=0.002) and dominant model (TT+CT vs CC: OR=0.816, 95%CI=0.678 to 0.982, p=0.032) genetic models. However, allelic (T vs C: OR=0.882, 95%CI=0.738 to 1.055, p=0.169), homozygous (TT vs CC: OR=1.185, 95%CI=0.825 to 1.700, p=0.358) and recessive (TT vs CC+CT: OR=1.268, 95%CI=0.897 to 1.793, p=0.179) models did not show any risk. No evidence of publication bias was detected during the analysis. The results of present meta-analysis suggest that the MMP2 -1306 C>T polymorphism is significantly associated with reduced risk of cancer. However, further studies with consideration of different populations will be required to evaluate this relationship in more detail.

• Spatial Information Research
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• v.18 no.4
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• pp.129-140
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• 2010

Large portal sites such as Google, NAVER provide Various services based on the map. Thus, interest and demand of users who want to obtain the region-related information has been increased. And services that combine the regional information with the map are provided currently at the large portal sites. However, the existing services of large portal sites do not provide enough detailed information and are inconvenient because acquisition process of related information is repeated. Therefore, the system that enables users to obtain detailed information related on the specific region synthetically and easily is needed. In this paper, we propose a system model using map interface and knowledge-processing in order to build the system that is useful for acquiring regional information. The model consists of 3-Layers: 'Regional Information Web-Documents Layer', 'Unique Regional Information Layer', and "Map-Interface Layer'. The Integrated Region~Related Information Searching System based on the model is implemented through the following 4-steps: (1) extracting the keywords that represent specific region (2) collecting the related web pages (3) extracting a set of related keywords and computing an association between the keywords (4) implementing a user interface. We verified validity on the model we proposed. knowledge-processing algorithm using affinity matrix, and UI that help users conveniently search by applying the system to region of the Goyang City. This system integrates regional information existing merely individual 'information' and provides users the 'knowledge' that is newly produced and organized. Users can obtain various detailed regional information and easily get related information through this system.