• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.92-103
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• 2021

With the continuous acceleration of economic and social development, people gradually pay attention to their health, improve their living environment, diet, strengthen exercise, and even conduct regular health examination, to ensure that they always understand the health status. Even so, people still face many health problems, and the number of chronic diseases is increasing. Recently, COVID-19 has also reminded people that public health problems are also facing severe challenges. With the development of artificial intelligence equipment and technology, medical diagnosis expert systems based on big data have become a topic of concern to many researchers. At present, there are many algorithms that can help computers initially diagnose diseases for patients, but they want to improve the accuracy of diagnosis. And taking into account the pathology that varies from person to person, the health diagnosis expert system urgently needs a new algorithm to improve accuracy. Through the understanding of classic algorithms, this paper has optimized it, and finally proved through experiments that the combined classification algorithm improved by latent factors can meet the needs of medical intelligent diagnosis.

• The Journal of the Korea Contents Association
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• v.5 no.3
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• pp.227-235
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• 2005

Document filtering is a task of deciding whether a document has relevance to a specified topic. As Internet and Web becomes wide-spread and the number of documents delivered by e-mail explosively grows the importance of text filtering increases as well. In this paper, we treat document filtering problem as binary document classification problem and we proposed the News Filtering system based on the Bayesian Classifier. For we perform filtering, we make an experiment to find out how many training documents, and how accurate relevance checks are needed.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.14-33
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• 2018

The purpose of this study to analyze the informatization trends in Korea through objective newspaper data for the period from 1998 to 2017 for informatization and library in four newspapers including KyoungHyang Newspaper, Kookmin Ilbo, Hankyoreh and Hankookilbo. Based on the analysis results of metadata and related words using BIGKinds, a news big data system, this study presented analysis of simple frequency, classification and classification of the keywords 'information', 'informatization' and 'library'. Based on the results, we compared and analyzed the tendency of informatization in the media through comparison with the 'Information White Paper' which is the publication of government agencies and with research about the research topic of 4 academic journals in the Library and Information Science field. This study tried to interpret the trends of informatization based on the media and it is meaningful that we analyzed the big data of newspaper article which is the long term and time series data. Based on the results of the study, implications of the growth and development of libraries with domestic informatization were suggested. It is expected that we will be able to create a basic framework for developing library informatization policy through the further studies.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.151-176
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• 2021

As the information technology industry develops, various kinds of data are being created, and it is now essential to process them and use them in the industry. Analyzing and utilizing various digital data collected online and offline is a necessary process to provide an appropriate experience for customers in the industry. In order to create new businesses, products, and services, it is essential to use customer data collected in various ways to deeply understand potential customers' needs and analyze behavior patterns to capture hidden signals of desire. However, it is true that research using data analysis and UX methodology, which should be conducted in parallel for effective service development, is being conducted separately and that there is a lack of examples of use in the industry. In thiswork, we construct a single process by applying data analysis methods and UX methodologies. This study is important in that it is highly likely to be used because it applies methodologies that are actively used in practice. We conducted a survey on the topic to identify and cluster the associations between factors to establish customer classification and target customers. The research methods are as follows. First, we first conduct a factor, regression analysis to determine the association between factors in the happiness data survey. Groups are grouped according to the survey results and identify the relationship between 34 questions of psychological stability, family life, relational satisfaction, health, economic satisfaction, work satisfaction, daily life satisfaction, and residential environment satisfaction. Second, we classify clusters based on factors affecting happiness and extract the optimal number of clusters. Based on the results, we cross-analyzed the characteristics of each cluster. Third, forservice definition, analysis was conducted by correlating with keywords related to happiness. We leverage keyword analysis of the thumb trend to derive ideas based on the interest and associations of the keyword. We also collected approximately 11,000 news articles based on the top three keywords that are highly related to happiness, then derived issues between keywords through text mining analysis in SAS, and utilized them in defining services after ideas were conceived. Fourth, based on the characteristics identified through data analysis, we selected segmentation and targetingappropriate for service discovery. To this end, the characteristics of the factors were grouped and selected into four groups, and the profile was drawn up and the main target customers were selected. Fifth, based on the characteristics of the main target customers, interviewers were selected and the In-depthinterviews were conducted to discover the causes of happiness, causes of unhappiness, and needs for services. Sixth, we derive customer behavior patterns based on segment results and detailed interviews, and specify the objectives associated with the characteristics. Seventh, a typical persona using qualitative surveys and a persona using data were produced to analyze each characteristic and pros and cons by comparing the two personas. Existing market segmentation classifies customers based on purchasing factors, and UX methodology measures users' behavior variables to establish criteria and redefine users' classification. Utilizing these segment classification methods, applying the process of producinguser classification and persona in UX methodology will be able to utilize them as more accurate customer classification schemes. The significance of this study is summarized in two ways: First, the idea of using data to create a variety of services was linked to the UX methodology used to plan IT services by applying it in the hot topic era. Second, we further enhance user classification by applying segment analysis methods that are not currently used well in UX methodologies. To provide a consistent experience in creating a single service, from large to small, it is necessary to define customers with common goals. To this end, it is necessary to derive persona and persuade various stakeholders. Under these circumstances, designing a consistent experience from beginning to end, through fast and concrete user descriptions, would be a very effective way to produce a successful service.

• Korea journal of population studies
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• v.25 no.2
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• pp.193-230
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• 2002

Issues regarding "generation" are facing a renaissance during recent years. One of prevailing reasons for this development is the crisis of collective identities due to diverse contemporary socio-political circumstances and cultural characteristics of Korean society. However, it is often criticized that the sociological examination of this topic is rather in a obscure stage resulting from the inherent confusion and ambiguities mainly caused by the mixed usage of the concept. In this regard, this study explores the possibility of answering these critics and refining the systemic usage for the sociology of generation in the realm of social changes and social innovations. For this purpose, analytical classification of the concept based on various contextual typology are attempted.attempted.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.227-231
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• 2009

The aim of the research is to focus on the cognitive principles and to achieve human-level intelligence in referring context based browser history and the Windows history. One of the major problems faced by today's computer users is insufficient and single exclusive context based reference of the browser history and the Windows history. Today we search for the browser history and Windows history in different places even though the context is the same. For e.g., When working on a research paper or preparing a business presentation, a user may require to refer many web sites on the internet and various documents on the local computer. The browser can provide only time based history. The windows document history is also time based and limited to list only few documents. Hence, we propose a tool "Cognitive Based Context Aware Reference History Management Tool" which helps to access the exclusive reference of context and time based history in one place. The tool also proposes to store image history with urls and classifies images of a specific topic accessed in different time, bookmarks management and cross browser history management. These features are very useful as we can access all related documents (doc, docx, ppt, pptx, pdf, txt, and html), web pages, images and bookmarks in one place. The tool uses the cognitive principles like classification and association to achieve the purpose.

• Journal of Distribution Science
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• v.22 no.2
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• pp.21-30
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• 2024

Purpose: This study explores the development of zakat distribution studies and the integration of existing studies. This study is expected to complement a systematic literature review in the field of zakat distribution to inspire further research directions. Research design, data, and methodology: This research method uses a systematic literature review assisted by the Nvivo application and the PRISMA system, which selects from 427 articles to 53 articles to be analyzed based on publication and classification of the theme of its findings. This study describes publications, authors, themes, cited articles, and research themes. Results: This study shows the dominance of Malaysian writers and significant developments in 2020. In addition, the study shows the most popular articles based on the most citations and word cloud analysis. The primary topics of zakat distribution publications are management strategy, development, the zakat institution, and the recipient. Conclusions: The study advises that Future research could focus on zakat distribution's asnaf characteristics. Next, a study on administration expenses and scalability concerns in zakat collection and distribution planning can avoid wasting cash. This topic hinders zakat institutions' distribution services.

• Dementia and Neurocognitive Disorders
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• v.17 no.4
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• pp.156-162
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• 2018

Background and Purpose: Previous studies have reported conflicting results about the prevalence of seizures in Alzheimer's disease (AD). There are few epidemiological studies on this topic in Asia. Thus, the objective of this study was to examine demographic and clinical characteristics as well as incidence for seizures in AD patients compared to non-AD patients in a prospective, longitudinal, community-based cohort with a long follow-up. Methods: Data were collected from National Health Insurance Service-National Elderly Cohort (NHIS-elderly) Database to define patients with AD from 2004-2006 using Korean Classification Diseases codes G30 and F00. We performed a 1:5 case-control propensity score matching based on age, sex, and household income. We conducted Cox proportional hazards regression analysis to estimate the risk of epilepsy in AD patients. Results: In the cohort study, patients with AD had higher risk for epilepsy than those without AD, with hazard ratio of 2.773 (95% confidence interval [CI], 2.515-3.057). This study also showed that male gender and comorbidities such as hypertension, hyperlipidemia, diabetes, and chronic kidney disease increased the risk of developing epilepsy. Patients with AD had 1.527 (95% CI, 1.375-1.695) times higher mortality rate than those in the control group. Conclusions: AD patients have significantly higher risk of developing epilepsy than non-AD patients.

• Journal of The Korean Association For Science Education
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• v.44 no.3
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• pp.231-248
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• 2024

This study developed a chatbot for first-year high school students, employing open-source software and the Korean Sentence-BERT model for AI-powered document classification. The chatbot utilizes the Sentence-BERT model to find the six most similar Q&A pairs to a student's query and presents them in a carousel format. The initial dataset, built from online resources, was refined and expanded based on student feedback and usability throughout over the operational period. By the end of the 2023 academic year, the chatbot integrated a total of 30,819 datasets and recorded 3,457 student interactions. Analysis revealed students' inclination to use the chatbot when prompted by teachers during classes and primarily during self-study sessions after school, with an average of 2.1 to 2.2 inquiries per session, mostly via mobile phones. Text mining identified student input terms encompassing not only science-related queries but also aspects of school life such as assessment scope. Topic modeling using BERTopic, based on Sentence-BERT, categorized 88% of student questions into 35 topics, shedding light on common student interests. A year-end survey confirmed the efficacy of the carousel format and the chatbot's role in addressing curiosities beyond integrated science learning objectives. This study underscores the importance of developing chatbots tailored for student use in public education and highlights their educational potential through long-term usage analysis.