• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.372-380
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• 2010

Generally, data mining is the process of analyzing data from different perspectives and summarizing it into useful information that can be used to increase revenue, cuts costs, or both. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Data mining is one of the fastest growing field in the computer industry. Because of According to computer technology has been improving, Massive customer data has stored in database. Using this massive data, decision maker can extract the useful information to make a valuable plan with data mining. Data mining offers service providers great opportunities to get closer to customer. Data mining doesn't always require the latest technology, but it does require a magic eye that looks beyond the obvious to find and use the hidden knowledge to drive marketing strategies. Automotive market face an explosion of data arising from customer but a rate of increasing customer is getting lower. therefore, we need to determine which customer are profitable clients whom you wish to hold. This paper builds model of customer loyalty detection and analyzes customer buying patterns in automotive market with data mining using decision tree as a quinlan C4.5 and basic statics methods.

• Journal of the Korean Society for Library and Information Science
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• v.44 no.4
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• pp.33-59
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• 2010

Library 2.0 advocates a socially rich, multimedia enabled, user originated and communally innovative environment that poses significant opportunities for the libraries to evolve and make themselves even more relevant and significant for her users. This paper presents a case study of the National Library Board of Singapore, in playing a vital role to facilitate the realisation of a long-term key national program, The Singapore Memory (SM) Project. SM embraces the attributes of the Library 2.0 environment to enable the nation's memory to be collected, organised, preserved, discovered, researched, augmented and created. The output of is an evolving collection of knowledge assets on Singapore along a Singapore Memory Content Continuum of existing content that is steadily augmented with new content. The content will be collected across all formats, in any language, from Singaporeans and non-Singaporeans, from any institution and agency, from Singapore and abroad, and from official and unofficial sources. The utopian scenario of SM Project is that any person, community, group or institution who has ever experienced Singapore in any way or has any material on Singapore will engage actively in the contribution, discovery and creation of content for the project, and thus become advocates to further encourage and catalyse more contribution, discovery and creation. The paper outlines the key approaches, concepts and ideas for the project. An important element is the proliferation, exposure and accessibility of the rich contents envisaged in the project. The SM proliferation plan along with examples of how two existing resources, namely, the Singapore Infopedia, a database of articles on Singapore's history, culture, people and events 4 and NewspaperSG, an online resource of current and historic Singapore and Malayan newspapers, have been designed are presented to demonstrate how content can be exposed, searched and discovered.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.639-647
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• 2008

This study used the characteristics of the knowledge discovery and data mining algorithms to develop tailored hypertension follow up management model - hypertension care predictive model and hypertension care compliance segmentation model - for hypertension management using the Korea National Health Insurance Corporation database(the insureds’ screening and health care benefit data). This study validated the predictive power of data mining algorithms by comparing the performance of logistic regression, decision tree, and ensemble technique. On the basis of internal and external validation, it was found that the model performance of logistic regression method was the best among the above three techniques on hypertension care predictive model and hypertension care compliance segmentation model was developed by Decision tree analysis. This study produced several factors affecting the outbreak of hypertension using screening. It is considered to be a contributing factor towards the nation’s building of a Hypertension follow up Management System in the near future by bringing forth representative results on the rise and care of hypertension.

• Journal of The Korean Astronomical Society
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• v.52 no.6
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• pp.217-225
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• 2019

We apply a modified Convolutional Neural Network (CNN) model in conjunction with transfer learning to predict whether an active region (AR) would produce a ≥C-class or ≥M-class flare within the next 24 hours. We collect line-of-sight magnetogram samples of ARs provided by the SHARP from May 2010 to September 2018, which is a new data product from the HMI onboard the SDO. Based on these AR samples, we adopt the approach of shuffle-and-split cross-validation (CV) to build a database that includes 10 separate data sets. Each of the 10 data sets is segregated by NOAA AR number into a training and a testing data set. After training, validating, and testing our model, we compare the results with previous studies using predictive performance metrics, with a focus on the true skill statistic (TSS). The main results from this study are summarized as follows. First, to the best of our knowledge, this is the first time that the CNN model with transfer learning is used in solar physics to make binary class predictions for both ≥C-class and ≥M-class flares, without manually engineered features extracted from the observational data. Second, our model achieves relatively high scores of TSS = 0.640±0.075 and TSS = 0.526±0.052 for ≥M-class prediction and ≥C-class prediction, respectively, which is comparable to that of previous models. Third, our model also obtains quite good scores in five other metrics for both ≥C-class and ≥M-class flare prediction. Our results demonstrate that our modified CNN model with transfer learning is an effective method for flare forecasting with reasonable prediction performance.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2006.06a
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• pp.288-293
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• 2006

최근 반도체 개발 및 제조부문에서는 급속도로 성장한 Mobile 시장과 Digital Consumer Trend 에 주도적으로 대응하고자 빠른 속도의 기술적 변화를 추진하여 왔으며, 이에 따라 현장에서 발생하는 기술적 문제의 유형 또한 점점 복잡 다양해지고 있다. 기존 Commodity 제품의 경우, 세대 전환이 느리게 진행되어, 이에 수반되는 기술적 문제의 난이도와 그 발생 종류가 현재 대비 상대적으로 단순하였다. 그러나 최근 다품종 주문형 제품비중 확대로, 발생되는 문제점들이 Field Application 과 tight 한 연관성을 지니고 있어, 문제의 발생 경로, 원인 파악과 해결 대책 수립에 상당한 초기대응 시간을 필요하며, 관련 부서와의 실시간 협업 및 Cross-Checking을 통하지 않고서는 문제에 대한 최적 Solution 을 결정하기 힘든 현실이 되었다. 이러한 기술 이슈 해결 과정에 기 발생했던 유사 이슈 처리 과정 및 결과 자료가 문제 해결에 크게 기여할 수 있으나, 종래의 지식관리 시스템 체계로는 이러한 실무 형 지식을 획득하기 어려운 부분이 한계점으로 지적되고 있다. 본 논문에서는 이러한 문제점 개선이 가능한 실무형 지식 관리 (AKM: Actual Knowledge Management) 기반의 기술적 이슈 추적 관리 시스템(TITS: Technical Issue Tracking System) 구축 사례를 제시하고자 한다. TITS 는 1) 기술 이슈의 발의 및 전파 기능과 2) 이슈 해결을 위한 Action Item 부여 및 의견 교환 기능 3) 해결된 이슈의 처리 결과 등록 기능 4) 유사 이슈 사례 검색 기능 등의 크게 4 개 모듈오 구성 되어있다. 이 시스템을 통해 반도체 엔지니어들은 기술적 이슈의 발생 시점부터, 원안분석, 대책 협의 ; Action Item 수립 등 문제 해결 과정과 결과 등록 시점까지 Real time Tracking이 가능해 졌으며, 본 시스템을 통해 처리된 모든 기술적 이슈 정보는 Issue Case Database 에 분류 저장되어, 향후 유사 이슈 발생 시, 이를 활용함으로써, 빠른 초기 대응 및 문제 해결에 직접적인 도움을 받을 수 있게 되었다.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.6099-6104
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• 2015

Background: Previous studies investigating the association between miR-34b/c rs4938723 polymorphism and cancer risk showed inconclusive. Here, we performed meta-analysis to investigate the association between miR- 34b/c rs4938723 polymorphism and digestive cancer risk. Materials and Methods: Literature database including PubMed, OVID, Chinese National Knowledge Infrastructure (CNKI) were searched for publications concerning the association between the miR-34b/c rs4938723 polymorphism and digestive cancer risk. Results: A total of 6 studies consisting of 3246 cases and 3568 controls were included in this meta-analysis. The combined analysis suggested the miR-34b/c rs4938723 polymorphism significantly reduced digestive cancer risk under allelic model, homogeneous co-dominant model and recessive model (C vs T: OR=0.88, 95%CI=0.82-0.95, p-value=0.001; CC vs TT: OR =0.67, 95%CI=0.57-0.80, p-value=0.000; CC vs TT/TC: OR=0.68, 95%CI=0.58-0.80, p-value=0.000). Q-test and I2 test revealed no significant heterogeneity in all genotype comparisons. The Begger's funnel plot and Egger's test did not show significant publication bias. Conclusions: The current evidence supports the conclusion that the miR-34b/c rs4938723 polymorphism decreases an individual's susceptibility to digestive cancers.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.7
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• pp.3267-3271
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• 2014

Background: Several studies have investigated the association between methionine synthase reductase (MTRR) A66G polymorphism and breast cancer risk, but controversial results were yielded. Therefore, we performed a meta-analysis to provide a more robust estimate of the effect of this polymorphism on susceptibility to breast cancer. Materials and Methods:Case-control studies investigating the relationship between MTRR A66G polymorphism and breast cancer risk were included by searching PubMed, EMBASE, China National Knowledge Infrastructure and Wanfang Database. Either fixed-effects or random-effects models were applied to calculate odds ratios(ORs) and 95% confidence intervals (CIs) by RevMan5.2 software. Results: A total of 9 studies bearing 7,097 cases and 7,710 controls were included in the meta-analysis. The results were that the combined ORs and 95%CIs of MTRR 66AG, GG, (AG+GG) genotypes were 0.98(0.91-1.05), 1.06(0.97-1.16) and 1.02(0.94-1.10), respectively with p=0.52, 0.19 and 0.65. We also performed subgroup analysis by specific ethnicity. The results of the combined analysis of MTRR 66AG, GG, (AG+GG) genotypes and breast cancer in Asian descent were Z=0.50, 0.53 and 0.21, with p all>0.05; for breast cancer in Caucasian descent, the results were Z=1.14, 1.65 and 0.43, with p all>0.05. Conclusions: Our findings suggested that MTRR A66G polymorphism was not associated with breast cancer susceptibility.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.8
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• pp.4553-4557
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• 2013

Objective: The purpose of this study was to identify genes related to bladder cancer with samples from normal and disease cases by microarray chip. Methods: After downloading the gene expression profile GSE3167 from Gene Expression Omnibus database which includes 50 bladder samples, comprising 9 normal and 41 disease samples, differentially expressed genes were identified with packages in R language. The selected differentially expressed genes were further analyzed using bioinformatics methods. Firstly, molecular functions, biological processes and cell component analysis were researched by software Gestalt. Then, software String was used to search interaction relationships among differentially expressed genes, and hub genes of the network were selected. Finally, by using plugins of software Cytoscape, Mcode and Bingo, module analysis of hub-genes was performed. Results: A total of 221 genes were identified as differentially expressed by comparing normal and disease bladder samples, and a network as well as the hub gene C1QBP was obtained from the network. The C1QBP module had the closest relationship to production of molecular mediators involved in inflammatory responses. Conclusion: We obtained differentially expressed genes of bladder cancer by microarray, and both PRDX2 and YWHAZ in the module with hub gene C1QBP were most significantly related to production of molecular mediators involved in inflammatory responses. From knowledge of inflammatory responses and cancer, our results showed that, the hub gene and its module could induce inflammation in bladder cancer. These related genes are candidate bio-markers for bladder cancer diagnosis and might be helpful in designing novel therapies.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.2241-2247
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• 2012

Objective: This qualitative study retrospectively examined the experience and psychological impact of contralateral prophylactic mastectomy (CPM) among Southern Chinese females with unilateral breast cancer history who underwent BRCA1/2 genetic testing. Limited knowledge is available on this topic especially among Asians; therefore, the aim of this study was to acquire insight from Chinese females' subjective perspectives. Methods: A total of 12 semi-structured in-depth interviews, with 11 female BRCA1/BRCA 2 mutated gene carriers and 1 non-carrier with a history of one-sided breast cancer and genetic testing performed by the Hong Kong Hereditary Breast Cancer Family Registry, who subsequently underwent CPM, were assessed using thematic analysis and a Stage Conceptual Model. Breast cancer history, procedures conducted, cosmetic satisfaction, pain, body image and sexuality issues, and cancer risk perception were discussed. Retrieval of medical records using a prospective database was also performed. Results: All participants opted for prophylaxis due to their reservations concerning the efficacy of surveillance and worries of recurrent breast cancer risk. Most participants were satisfied with the overall results and their decision. One-fourth expressed different extents of regrets. Psychological relief and decreased breast cancer risk were stated as major benefits. Spouses' reactions and support were crucial for post-surgery sexual satisfaction and long-term adjustment. Conclusions: Our findings indicate that thorough education on cancer risk and realistic expectations of surgery outcomes are crucial for positive adjustment after CPM. Appropriate genetic counseling and pre-and post-surgery psychological counseling were necessary. This study adds valuable contextual insights into the experiences of living with breast cancer fear and the importance of involving spouses when counseling these patients.

• Journal of the Korea Computer Industry Society
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• v.2 no.9
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• pp.1175-1182
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• 2001

One to one Marketing (a.k.a. database marketing or relationship marketing) is one of the many fields that will benefit from the electronic revolution and shifts in consumer sales and advertising. As a component of intelligent customer services on Internet storefront, this paper describes technology of providing personalized advertisement using the market basket analysis, a well-Known data mining technique. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customer's data. However, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed Knowledge base. In this paper, using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store.