• The Journal of Bigdata
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• v.2 no.1
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• pp.41-48
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• 2017

Recently, the popularity of the recommendation system and the evaluation of the performance of the algorithm of the recommendation system have become important. In this study, we used modeling and RMSE to verify the effectiveness of various algorithms in movie data. The data of this study is based on user-based collaborative filtering using Pearson correlation coefficient, item-based collaborative filtering using cosine correlation coefficient, and item-based collaborative filtering model using singular value decomposition. As a result of evaluating the scores with three recommendation models, we found that item-based collaborative filtering accuracy is much higher than user-based collaborative filtering, and it is found that matrix recommendation is better when using matrix decomposition.

• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.513-521
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• 2010

Most of universities have carried out course evaluation to apply the performance appraisal for professor. But, course evaluation depends on characteristics of each class such as class size, type of lecture, evaluator's grade and so on. As the results, such characteristics of each class lead to serious bias which makes lecturers distrust the course evaluation results. Hence, we propose a equating method for the course evaluation by regression analysis which use stepwise variable selection. And we compare proposed method with the other method by Cho et al. (2009) with respect to efficiencies. Also we give the example to which the method is applied.

• The Journal of Bigdata
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• v.4 no.2
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• pp.175-183
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• 2019

Drop-out issue is one of the challenges of cyber university. There are about 130,000 students enrolled in cyber universities, but the dropout rate is also very high. To lower the dropout rate, cyber universities invest heavily in learning analytics. Some cyber universities analyze the possibility of dropout and actively support students who are more likely to drop out. The purpose of this paper is to identify the learning data affecting the dropout prediction index. As a result of the analysis, it is confirmed that number of lessons(progress), credits, achievement and leave of absence have a significant effect on dropout rate. It is necessary to increase the accuracy of the prediction model through post-test on the student dropout prediction index.

• Journal of Haehwa Medicine
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• v.25 no.1
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• pp.63-69
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• 2016

이 임상례는 근육 경직으로 인한 견비통에 태충혈이 유효함을 제시하고 있다. 환자의 주관적인 만족도를 평가하기 위해 점수식 평점 척도(Numerical rating scale;NRs)를 측정하였고 어깨 경직의 객관적인 호전 정도를 평가하기 위하여 양측 견정혈의 통증 통각 역치(Pressure pain threshold;PPT)와 어깨 외전력, 어깨관절의 외전시 가동범위(Range of motion;ROM)을 측정하였다. 양측 태충혈에 15분간 유침 후 NRS는 5에서 2로 감소하였다. 치료 전 왼쪽 견정혈의 PPT는 19N이었고 오른쪽은 22N이었다. 치료 후 왼쪽 견정혈의 PPT는 22N이었고 오른쪽은 27N이었다. 치료 전 견관절의 외전력은 왼쪽에서 29N, 오른쪽에서 22N으로 측정되었다. 치료후 견관절의 외전력은 왼쪽에서 33N, 오른쪽에서 22N으로 측정되었다. 견관절 ROM은 치료 전과 후 동일하게 왼쪽 관절 170도, 오른쪽 관절 165도로 나타났다. 결론적으로, 태충혈 자극은 어깨의 경직을 해소하고 어깨 근력을 강화하는 것으로 나타났다. 또한 그것은 상부 승모근의 압통을 감소시킬 수 있다. 이러한 측면에서, 태충혈의 효과에 대해서 보다 추가적인 연구가 필요할 것으로 보인다.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.411-422
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• 2014

This study analyzed how average GPA (grade point average) changes as the number of completed semesters increases based on the estimates of intercept, slope, and quadratic term. The students included in this study are those who was admitted in 2011 and took 6 consecutive semesters. More precisely, it was analyzed if intercept, slope and quadratic term of average GPA were different between gender and selection method. The results showed that the intercept was different between selection method, the slope was different between gender, but the quadratic term was different between neither selection method nor gender.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.113-125
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• 2017

Customers have been affected by others' opinions when they make a purchase. Thanks to the development of technologies, people are sharing their experiences such as reviews or ratings through online or social network services, However, although ratings are intuitive information for others, many reviews include only texts without ratings. Also, because of huge amount of reviews, customers and companies can't read all of them so they are hard to evaluate to a product without ratings. Therefore, in this study, we propose a methodology to predict ratings based on reviews for a product. In a methodology, we first estimate the topic-review matrix using the Latent Dirichlet Allocation technic which is widely used in topic modeling. Next, we predict ratings based on the topic-review matrix using the artificial neural network model which is based on the backpropagation algorithm. Through experiments with actual reviews, we find that our methodology can predict ratings based on customers' reviews. And our methodology performs better with reviews which include certain opinions. As a result, our study can be used for customers and companies that want to know exactly a product with ratings. Moreover, we hope that our study leads to the implementation of future studies that combine machine learning and topic modeling.

• Journal of Information Technology Services
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• v.16 no.4
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• pp.161-176
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• 2017

Recently, most of the users can easily get access to a variety of information sources about companies, products, and services through online channels. Therefore, the online user evaluations are becoming the most powerful tool to generate word of mouth. The user's evaluation is provided in two forms, quantitative rating and review text. The rating is then divided into an overall rating and a detailed rating according to various evaluation criteria. However, since it is a burden for the reviewer to complete all required ratings for each evaluation criteria, so most of the sites requested only mandatory inputs for overall rating and optional inputs for other evaluation criteria. In fact, many users input only the ratings for some of the evaluation criteria and the percentage of missed ratings for each criteria is about 40%. As these missed ratings are the missing values in each criteria, the simple average calculation by ignoring the average 40% of the missed ratings can sufficiently distort the actual phenomenon. Therefore, in this study, we propose a methodology to predict the rating for the missed values of each criteria by analyzing user's evaluation information included the overall rating and text review for each criteria. The experiments were conducted on 207,968 evaluations collected from the actual hotel evaluation site. As a result, it was confirmed that the prediction accuracy of the detailed criteria ratings by the proposed methodology was much higher than the existing average-based method.

• Food Science and Preservation
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• v.11 no.2
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• pp.148-153
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• 2004

The organoleptic properties of granule tea was optimized for granulation of Polygonatum sibiricum Delar(Dunggulle) tea for exclusion of scorched smell and increase of consumption. The length of 2 mm was suitable to cutting size of Dunggulle for preparation of the roasted Dunggulle. The optimum sensory conditions for aroma of Dunggulle granule tea showing 7.85 organoleptic score were 80.61% in ratio of Dunggulle extracts to total extracts, 12.77% in content of total extracts and 37.33% in rate of glucose to total sugar. The highest score of overall palatability was 5.96 at 61.11% in rate of Dunggulle extracts to total extracts, 13.79% in content of total extracts, and 60.92% in rate of glucose to total sugar.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.423-424
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• 2016

본 연구는 30대, 40대 남성 근로자의 심뇌혈관질환 인식, 예방에 대한 태도, 건강행위 간의 관계를 알아보고, 건강행위에 미치는 영향요인을 파악하여 30,40대 남성 근로자의 건강행위를 증진키기 위한 기초 자료를 제공하기 위하여 시도되었다. 연구대상자는 G도 J, S시에 소재한 회사에 근무하는 30대, 40대 남성 근로자를 대상으로 하였으며, 자료 수집은 심혈관질환 인식, 뇌혈관질환 인식, 예방에 대한 태도, 건강행위 도구를 통하여 설문 조사하였다. 자료 분석은 SPSS Win 21.0 프로그램을 이용하여 분석하였다. 연구결과 대상자의 평균 평점은 심혈관질환 인식 정도는 17.99점, 뇌혈관질환 인식 정도는 5.21점, 예방에 대한 태도는 3.95점, 건강행위 정도는 2.82점으로 나타났다. 대상자의 심혈관질환 인식, 뇌혈관질환 인식, 예방에 대한 태도는 건강행위와 양의 상관관계가 있는 것으로 나타났다. 대상자의 건강행위에 영향을 미치는 요인으로 결혼상태, 심혈관질환 인식 순이었으며, 전체 설명력은 14.6%이었다. 본 연구를 바탕으로 심뇌혈관질환 예방을 위한 건강행위의 교육적 시사점과 후속연구에 대한 제언을 하였다.

• Journal of the Korean Society for information Management
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• v.28 no.3
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• pp.31-46
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• 2011

Information literacy of the individuals affects their competitive capability significantly by providing problem solving skills in the short run, and by enabling life-long learning in the long run. This study examines if information literacy capacity has any relationship with individuals' achievement level through the experiment with college student subject group. As evidences for individual achievement level, we adopted GPA's(grade point average) of students. As a result, it was confirmed that information literacy and academic achievements has positive relationship. Additionally, it has been found that this relationship has a tendency of sustaining for a significant period. These experiment results would serve as a rationale for providing information literacy courses in the academic curriculum.