• The Journal of the Korea Contents Association
• /
• v.7 no.11
• /
• pp.23-33
• /
• 2007

The collaborative filtering has used the nearest neighborhood method based on the preference and the similarity using the Pearson correlation coefficient. Therefore, it does not reflect content of the items and has the problems of the sparsity and scalability as well. the item-based collaborative filtering has been practically used to improve these defects, but it still does not reflect attributes of the item. In this paper, we propose the user and item based collaborative filtering using the classification property and Naive Bayesian to supplement the defects in the existing recommendation system. The proposed method complexity refers to the item similarity based on explicit data and the user similarity based on implicit data for handing the sparse problem. It applies to the Naive Bayesian to the result of reference. Also, it can enhance the accuracy as computation of the item similarity reflects on the correlative rank among the classification property to reflect attributes.

• The Journal of the Korea Contents Association
• /
• v.12 no.6
• /
• pp.475-485
• /
• 2012

The purpose of this research study was to identify the factors that influence comsumer who make decisions on preferred coffee types. Data was collected for a month from September $12^{th}$ to October $10^{th}$, 2010 from 807 participants who visited a cafe' in Seoul. The Limdep(LIMited DEPendent) 8.0 program was used in analyzing the determinants for preferred types of coffee using the multinomial logit model(MNL) approach. The results revealed that there were four taste preference groups being Espresso, Americano, Cafe' Late, and Cafe' Mocha ; as well as confirming that demographic characteristics influenced the coffee selection attributes, type of packaging, preferred coffee brand, and visit frequencies. This study found seven coffee selection attributes were significant factors in influencing patrons choices for purchasing speciality coffee being age range, profession, packing status, elation, superficial appearance, weight control, and habitual, respectively. The research reflects the coffee selection attributes by the customers' preference and concludes that it would be helpful to make marketing strategy for particular coffee brands.

• Journal of KIISE:Software and Applications
• /
• v.26 no.12
• /
• pp.1455-1467
• /
• 1999

소프트웨어 품질을 정의하기 위한 여러 가지 소프트웨어 품질 모형(SQM : Software Quality Model)이 개발되어 왔다. 이 모형들은 두 가지 목적을 가진다. 한 가지는 소프트웨어 품질 측정이고, 또 다른 목적은 개발 프로세스에서의 소프트웨어 품질 제어이다. 국제 표준인 ISO/IEC 9126은 소프트웨어 측정을 위한 소프트웨어 품질 모형을 제시하였다. ISO/IEC 9126의 품질 모형은 사용 관점에서 소프트웨어 품질을 정의한 모형이다. 이 모형은 개발 프로세스에서의 품질 제어를 하는 측면에서는 불완전한 모형이다. 소프트웨어의 품질이 프로세스 내에서 어떻게 만들어지는지 볼 수 없는 모형이기 때문이다. 따라서, 개발 관점에서의 소프트웨어 품질 모형이 필요하다.본 논문에서는 사용 관점인 ISO/IEC 9126 품질 모형을 기반으로 하여 개발 관점에서의 소프트웨어 품질 모형을 제안한다. 이 모형은 ISO/IEC 9126과 같이 하위 품질 요소가 중복되지 않는 계층적 품질 모형이면서, 개발 프로세스 내에서 제어 가능한 제품 특성에 기반을 둔 개발 관점의 소프트웨어 품질 모형이다. 본 논문에서는 소프트웨어 품질 모형 구축 시, 품질 속성간의 선후조건관계를 설정하여 품질 속성간 중복되었던 제품 특성을 한 품질 속성 내 귀속시킨다. 품질 속성 별 제품 특성을 기반으로, 프로세스 내에서 제품 특성을 측정하는 메트릭스를 제안한다. 본 논문에서 제안한 품질 모형과 ISO/IEC 9126을 비롯한 기존 품질 모형과 비교 분석한다.Abstract Several SQMs(Software Quality Models) have been developed to define a software quality. These models have two goals. One is to measure a software quality, the other is to control a software quality. The SQM of ISO/IEC 9126 is defined from the user's viewpoint. This model is an incomplete model in controlling a software quality in the development process. Since this model cannot show how to build a high quality software, the SQM of the developer's view is needed.We suggest the SQM of the developer's view. This model is a completely hierarchical model and is based on product properties. For this model, we define implicative relations among quality attributes for 1:m relations of quality attributes and product properties. So, we solve the problem of a quality attribute overlapping with other quality attributes. We suggest metrics based on our SQMs. Further, we evaluate our SQM by comparing our SQM with other SQMs.

• Culinary science and hospitality research
• /
• v.21 no.4
• /
• pp.271-283
• /
• 2015

The purpose of current study was to find differences of selected attributes and visitors of responses according to their lifestyle as perceived by Pocheon Yidong-BBQ-Galbi Festival participants. Survey method was employed and total 370 data was used for statistical analysis. The results of factor analysis showed that three factors were extracted from lifestyle(Activity, Example, Commonness), and four factors were found from festival selection attribute(Food, Service, Program, Cleanliness). In addition, three clusters(Outgoing personality, Gentle character, Normal character) were extracted from the result of cluster analysis. The result of chi-square shows that selection attributes are significantly different by clusters of festival. Therefore the festival host need to focus on various kinds of BBQ along with diverse foods and activities to make attractive cultual experience festival for visitors who visited with family. Additionally, all selection attributes except clearness have significantly influence on responsive relationship. Thus, the organizer should make an effort to provide high quality of various selection attributes. Current study will be contribute to develop various and fascinating local festival expecially related to food.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.6
• /
• pp.796-801
• /
• 2009

In medical practice, the diagnosis or prediction models requiring complicated computations are not widely recognized due to difficulty in interpreting the course of reasoning and the complexity of computations. Medical personnel have used the nomograms which are a graphical representation for numerical relationships that enables to easily compute a complicated function without help of computation machines. It has been widely paid attention in diagnosing diseases or predicting the progress of diseases. A nomogram is constructed from a set of clinical data which contain various attributes such as symptoms, lab experiment results, therapy history, progress of diseases or identification of diseases. It is of importance to select effective ones from available attributes, sometimes along with parameters accompanying the attributes. This paper introduces a nomogram construction method that uses a naive Bayesian technique to construct a nomogram as well as a genetic algorithm to select effective attributes and parameters. The proposed method has been applied to the construction of a nomogram for a real clinical data set.

• The Journal of Korean Association of Computer Education
• /
• v.5 no.1
• /
• pp.35-43
• /
• 2002

By entering the information society, the trend of increasing use of the cyber education to deliver high-Quality educational programs is likely to continue. For instance, supported by the government agencies, central officials training institute is expending vast amounts of money for the installation of cyber education programs. However, much of the research that has been done concerns the discrepancy between the potential and the actual use of technology in the field of education and training. The intent of this study was to identify the decision of the adoption of cyber education among national officials who had just peceived the existence the cyber education programs which would be used for their professional training and development, and to investigate the relationships between the Rogers' five attributes of innovation (relative advantage, compatibility, easy of use, observability, trialiability) and their decision of adoption. The results of the study generally concurred with Rogers diffusion of innovation theory revealing that perceived compatibility, easy of use, and observability of cyber education are significant predictors of decision to participate in cyber education.

• Journal of Korea Society of Industrial Information Systems
• /
• v.20 no.4
• /
• pp.1-9
• /
• 2015

This paper proposes CAC method that is more efficient for RRM using game theory combined with Multiple Attribute Decision Making(MADM). Because users request services with different Quality of Service(QoS), the network preference values to alternative networks for each service are calculated by MADM methods such as Grey Relational Analysis(GRA), Simple Additive Weighting(SAW) and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS). According to a utility function representing preference value, non-cooperative game is played, and then network provider select the requested service that provide maximum payoff. The appropriate service is selected through Nash Equilibrium that is the solution of game and the game is played repeated. We analyze two overlaid networks among four Wireless LAN(WLAN) systems with different properties. Simulation results show that proposed MADM techniques have same outcomes for every game round.

• The KIPS Transactions:PartD
• /
• v.14D no.5
• /
• pp.491-500
• /
• 2007

In order to classify and manage on-line trading goods, the product classification scheme must be maintained. In most systems for handling product information, the classification scheme is managed manually by experts, which in general incurs a lot of time and cost. Effective management of classification system becomes more important as rapid development of industry expedites diversity and convergence of goods and services. There have been many researches on developing classification scheme, and continuing in this line of research, this paper proposes a new method for automatic generation of product classification scheme. Our main idea starts from the concept that a product is a set of attributes, and we propose a novel algorithm for automatically creating hierarchical classification scheme by utilizing inclusive relationships between products. We then prove the effectiveness of proposed algorithm by conducting an experiment.

• The Korean Journal of Applied Statistics
• /
• v.33 no.6
• /
• pp.833-842
• /
• 2020

Global platforms such as Netflix, Amazon, and YouTube have developed a precise recommendation system based on various information from large set of customers and many of the items recommended here are leading to actual purchases. In this paper, a cluster analysis was conducted according to the attribute of the content, expecting that there would be a difference in user preferences according to the attribute of the recommended content. Gower distance was used for use regardless of the type of variables. In this paper, using the data of movie rating site 'The Movie Dataset', the users were grouped hierarchically and recommended movies based on genre, director and actor variables. To evaluate the recommended systems proposed, user group was divided into train set and test set to examine the precision. The results showed that proposed algorithms have far higher precision than UBCF.

• The Journal of the Korea Contents Association
• /
• v.22 no.10
• /
• pp.271-278
• /
• 2022

MyData service integrates and manages user's personal data such as finance, credit, etc, and is expected to provide useful information to the user as personal data in various fields are gradually integrated. Discovering factors that affect the intention to use of MyData service is a very important topic for understanding that service. To this end, in this study, the attributes of the MyData service were derived, and the derived service attributes were grouped together by using factor analysis. As a result, we found four factors such as "convenience", "usefulness", "security", and "control". After that, we established our research model to analyze the causal relationship between these four factors and the intention to use of MyData service. According to the analysis results, among the factors of the MyData service attribute, "convenience", "usefulness", and "control" had a significant effect, and "security" did not have a significant effect. In particular, it was confirmed that "control" had the greatest influence on the intention to use. This study suggests that MyData service provider need to make users recognize they are controlling their data and develop services that provide various benefits to users.