• 보건교육건강증진학회지
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• 제30권3호
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• pp.59-73
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• 2013

Objectives: The study is aimed at examining the individual reasons and regional/environmental factors of online search on suicide using social big data to predict practical behaviors related to suicide and to develop an online suicide prevention system on the governmental level. Methods: The study was conducted using suicide-related social big data collected from online news sites, blogs, caf$\acute{e}$s, social network services and message boards between January 1 and December 31, 2011 (321,506 buzzes from users assumed as adults and 67,742 buzzes from those assumed as teenagers). Technical analysis and development of the suicide search prediction model were done using SPSS 20.0, and the structural model, nd multi-group analysis was made using AMOS 20.0. Also, HLM 7.0 was applied for the multilevel model analysis of the determinants of search on suicide by teenagers. Results: A summary of the results of multivariate analysis is as follows. First, search on suicide by adults appeared to increase on days when there were higher number of suicide incidents, higher number of search on drinking, higher divorce rate, lower birth rate and higher average humidity. Second, search on suicide by teenagers rose on days when there were higher number of teenage suicide incidents, higher number of search on stress or drinking and less fine dust particles. Third, the comparison of the results of the structural equation model analysis of search on suicide by adults and teenagers showed that teenagers were more likely to proceed from search on stress to search on sports, drinking and suicide, while adults significantly tended to move from search on drinking to search on suicide. Fourth, the result of the multilevel model analysis of determinants of search on suicide by teenagers showed that monthly teenagers suicide rate and average humidity had positive effect on the amount of search on suicide. Conclusions: The study shows that both adults and teenagers are influenced by various reasons to experience stress and search on suicide on the Internet. Therefore, we need to develop diverse school-level programs that can help relieve teenagers of stress and workplace-level programs to get rid of the work-related stress of adults.

• 동의신경정신과학회지
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• 제34권1호
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• pp.13-21
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• 2023

Objectives: The aim of this study was to analyze correlations among searches of hwa-byung, depression, and suicide using big data. Methods: Keywords searches were performed using both Google Trends and Naver Data Lab on December 13, 2022. From 2016 to 2022, search results for keywords 'hwa-byung', 'depression', and 'suicide' were extracted with a score between 0 and 100 in terms of relative search popularity (RSP). Monthly time analysis, correlation analysis, and regional analysis were then conducted for these scores. Results: Regardless of the search period, RSP for both portal sites was in the order of 'suicide', 'depression', and 'hwa-byung'. Over time, search for 'depression' tended to increase in Google (slope: 0.0092), whereas search for 'hwa-byung' showed a slight increase in Naver (slope: 0.0024). Correlation coefficient for search terms 'depression' and 'suicide' was 0.3969 in Google Trends and 0.4459 in Naver Data Lab, showing clear positive correlations. On the other hand, there was little correlation between search results of 'hwa-byung' and 'depression' or between 'hwa-byung' and 'suicide'. However, compared to males, females showed higher positive associations between search results of 'hwa-byung' and 'depression' and between 'hwa-byung' and 'suicide'. Search terms 'depression' and 'suicide' showed high RSPs in most regions in South Korea. However, 'hwa-byung' had distinct regional differences in terms of RSP. Conclusions: Results of this study will help us understand Korean public's perception of the relevance of hwa-byung, depression, and suicide and plan future research in this topic. In addition, findings of this study may provide future public health implications for reducing the high suicide rate in Korea.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.911-917
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• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• 대한가정학회지
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• 제48권9호
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• pp.41-54
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• 2010

This study attempted to determine how the subjective knowledge related to a consumer's life cycle influences their information search in the decision making process. The data was collected using a total of 349 questionnaires for the final analysis of this study. SPSS 12.0 for windows was used for the data analysis and the detailed analyses included descriptive analysis, factor analysis, reliability tests, one way ANOVA, multiple regression analysis and t-tests. The results of this study showed that there are differences in the subdivisions of subjective knowledge of apparel according to the consumer's life cycle and there is a difference in the types of information searches according to the consumer's subjective knowledge, and the subdivisions of subjective knowledge of the consumers influence their information search. This study showed that although it affected the internal search, the media search, and the store search, it did not influence the personal search in the decision making process.

• 대한족부족관절학회지
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• 제25권3호
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• pp.126-132
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• 2021

Purpose: This study examined whether there are seasonal variations in the number of plantar fasciitis cases from the database of the Korean Health Insurance Review & Assessment Service and an internet search of the volume data related to plantar fasciitis and whether there are correlations between variations. Materials and Methods: The number of plantar fasciitis cases per month was acquired from the Korean Health Insurance Review & Assessment Service from January 2016 to December 2019. The monthly internet relative search volumes for the keywords "plantar fasciitis" and "heel pain" were collected during the same period from DataLab, an internet search query trend service provided by the Korean portal website, Naver. Cosinor analysis was performed to confirm the seasonality of the monthly number of cases and relative search volumes, and Pearson and Spearman correlation analysis was conducted to assess the correlation between them. Results: The number of cases with plantar fasciitis and the relative search volume for the keywords "plantar fasciitis" and "heel pain" all showed significant seasonality (p<0.001), with the highest in the summer and the lowest in the winter. The number of cases with plantar fasciitis was correlated significantly with the relative search volumes of the keywords "plantar fasciitis" (r=0.632; p<0.001) and "heel pain" (r=0.791; p<0.001), respectively. Conclusion: Both the number of cases with plantar fasciitis and the internet search data for related keywords showed seasonality, which was the highest in summer. The number of cases showed a significant correlation with the internet search data for the seasonality of plantar fasciitis. Internet big data could be a complementary resource for researching and monitoring plantar fasciitis.

• Journal of Information Technology Applications and Management
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• 제16권1호
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• pp.21-36
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• 2009

As the World Wide Web (WWW) has become a major channel for information delivery, the data accumulated in the Internet increases at an incredible speed, and it derives the advances of information search technologies. It is the search engine that solves the problem of information overloading and helps people to identify relevant information. However, as search engines become a powerful tool for finding information, the opportunities of plagiarizing have increased significantly in e-Learning. In this paper, we developed an online plagiarism detection system for detecting plagiarized documents that incorporates the functions of search engines and acts in exactly the same way of plagiarizing. The plagiarism detection system uses morpheme analysis to improve the performance and sentence-based comparison to investigate document comes from multiple sources. As a result of applying this system in e-Learning, the performance of plagiarism detection was improved.

• 한국의류산업학회지
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• 제17권5호
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• pp.731-740
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• 2015

Mobile (smartphone) search engine marketing is increasingly important. Accordingly, the development of visual apparel search technology to obtain easier and faster access to visual information in the apparel field is urgently needed. This study helps establish a proper classifying system for an apparel search after an analysis of search techniques for apparel search applications and existing domestic and overseas apparel sites. An annotation technique is developed in accordance with visual attributes and apparel categories based on collected data obtained by web crawling and apparel images collecting. The categorical composition of apparel is divided into wearing, image and style. The web evaluation site traces the correlations of the apparel category and apparel factors as dependent upon visual attributes. An appraisal team of 10 individuals evaluated 2860 pieces of merchandise images. Data analysis consisted of correlations between apparel, sleeve length and apparel category (based on an average analysis), and correlation between fastener and apparel category (based on an average analysis). The study results can be considered as an epoch-making mobile apparel search system that can contribute to enhancing consumer convenience since it enables an effective search of type, price, distributor, and apparel image by a mobile photographing of the wearing state.

• 패션비즈니스
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• 제16권2호
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• pp.62-73
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• 2012

This study is intended to analyze the effect of fashion consumer's information search on satisfaction with advertisement and the intent to reuse depending on type of advertisement. The survey of the men and women in their 20s and 30s living in Seoul and metropolitan area was conducted for data collection, beginning in 17th through 24th, October 2011. Total 355 copies of questionnaire were used for final data analysis and reliability analysis, factorial analysis and multiple regression analysis were carried out using SPSS 16.0. The results were as follows. First, for banner, e-mail and search advertisement, constant information search had influence on convenience for use and satisfaction with information, and for e-mail advertisement, information search appeared to have had effect on satisfaction with information. Second, constant information search by type of advertisement had effect on intent to reuse. Third, convenience for use, information and satisfaction with the interest by Internet user had influence on the intent to reuse, while for the user of search advertisement, convenience for use and satisfaction with information had effect on the intent to reuse.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제10권6호
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• pp.223-234
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• 2021

4차 산업 혁명 시대의 도래에 따라 쇼핑의 행태는 더욱 빠르게 오프라인에서 온라인으로 이동하고 있다. 온라인 쇼핑에서 고객의 정보요구를 가장 집약적으로 보여주는 것이 바로 검색 질의이다. 하지만 검색 분야에서도 검색 질의 관련 연구 사례는 많지 않으며 대부분의 검색 질의 연구 분야 선행 연구들은 연구자의 정성적인 판단에 근거하여 제한적인 주제와 데이터 기반으로 연구되어 왔다. 이에 본 연구는 검색 질의 연구 분야에 기계학습을 적용하여 검색 질의와 검색 이후 이용자가 조회한 문서명 로그를 기반으로 토픽모델링 수행 후 검색 질의 주제를 정의함으로써 데이터 기반의 정량적 방법론으로 15개의 검색 질의 주제 유형을 정의하였다. 또한 기존 검색어 자체만을 보고 판단하던 주제 유형에서 나아가 검색 행동특성을 반영한 유형을 정의하기 위하여 주성분 분석을 통해 주요 변수를 추출 후 각 주제별 검색 행동특성을 분석함으로써 검색 탐색 활성도, 상품 관여도에 따른 4가지의 새로운 검색 질의 유형 분류체계를 제시하였다. 본 연구결과는 효과적인 검색서비스 구축 및 검색 시스템 개발에 기여할 것으로 기대된다.

• 웰빙융합연구
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• 제6권1호
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• pp.23-31
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• 2023

Purpose: The purpose of this study is a preliminary study to develop a comprehensive information avoidance scale that includes various search contexts. Research design, data and methodology: This study is a part of exploratory sequential design of mixed method for the development of information avoidance scale. Based on the themes derived from the analysis of the in-depth interview data collected in the qualitative research of the first stage of the study, 45 preliminary items on information search and avoidance were constructed. The factors related to information searching included information recognition, information seeking purpose, and information search expectations. Individual, information, time, and system factors were related to information avoidance. Pearson's correlation analysis was performed for the correlation between factor items, and Cronbach's alpha analysis was performed for the reliability analysis of the items. Exploratory factor analysis was applied to examine the construct validity of 35 items of information avoidance. Results: Among the information avoidance items, one of the less relevant among information purpose items, two information factor items, and one time factor item were excluded. Conclusions: A secondary survey should be conducted to confirm the validity and reliability of the scale composed of adjusted items (35) based on the results of exploratory factor analysis. The strength of this preliminary scale is that it was developed based on vivid qualitative data of ordinary people who had experiences of search and avoidance in various search contexts.