• Journal of the Korean Data and Information Science Society
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• v.24 no.1
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• pp.117-124
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• 2013

Association rule of data mining techniques is the method to quantify the relationship between a set of items in a huge database, andhas been applied in various fields like internet shopping mall, healthcare, insurance, and education. There are three primary interestingness measures for association rule, support and confidence and lift. Confidence is the most important measure of these measures, and we generate some association rules using confidence. But it is an asymmetric measure and has only positive value. So we can face with difficult problems in generation of association rules. In this paper we apply the similarity measures by probabilistic interestingness measure (PIM) with all marginal proportions (AMP) to solve this problem. The comparative studies with support, confidences, lift, chi-square statistics, and some similarity measures by PIM with AMPare shown by numerical example. As the result, we knew that the similarity measures by PIM with AMP could be seen the degree of association same as confidence. And we could confirm the direction of association because they had the sign of their values, and select the best similarity measure by PIM with AMP.

• Journal of Intelligence and Information Systems
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• v.12 no.2
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• pp.33-48
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• 2006

The Semantic Web and its related technologies have been opening the era of information sharing via the Web. There are, however, several huddles still to overcome in the new era, and one of the major huddles is the issue of information integration, unless a single unified and huge ontology could be built and used which could address everything in the world. Particularly in the e-business area, the problem of information integration is of a great concern for product search and comparison at various Internet shopping sites and e-marketplaces. To overcome this problem, we proposed an ontology-driven mapping algorithm between heterogeneous product classification and description frameworks. We also peformed a comparative evaluation of the proposed mapping algorithm against a well-Down ontology mapping tool, PROMPT.

• Journal of the Korea Society of Computer and Information
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• v.19 no.2
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• pp.193-200
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• 2014

Due to the advent of ubiquitous computing environment, it is becoming a part of our common life style. And tremendous information is cumulated rapidly. In these trends, it is becoming a very important technology to find out exact information in a large data to present users. Collaborative filtering is the method based on other users' preferences, can not only reflect exact attributes of user but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. In this paper, we propose clustering method by user's features based on SOM for predicting purchase pattern in u-Commerce. it is necessary for us to make the cluster with similarity by user's features to be able to reflect attributes of the customer information in order to find the items with same propensity in the cluster rapidly. The proposed makes the task of clustering to apply the variable of featured vector for the user's information and RFM factors based on purchase history data. To verify improved performance of proposing system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• Journal of the Korea Society of Computer and Information
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• v.17 no.6
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• pp.163-172
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• 2012

Collaborative filtering which is used explicit method in a existing recommedation system, can not only reflect exact attributes of item but also still has the problem of sparsity and scalability, though it has been practically used to improve these defects. This paper proposes the personalized recommendation system using RFM method and k-means clustering in u-commerce which is required by real time accessablity and agility. In this paper, using a implicit method which is is not used complicated query processing of the request and the response for rating, it is necessary for us to keep the analysis of RFM method and k-means clustering to be able to reflect attributes of the item in order to find the items with high purchasablity. The proposed makes the task of clustering to apply the variable of featured vector for the customer's information and calculating of the preference by each item category based on purchase history data, is able to recommend the items with efficiency. To estimate the performance, the proposed system is compared with existing system. As a result, it can be improved and evaluated according to the criteria of logicality through the experiment with dataset, collected in a cosmetic internet shopping mall.

• Journal of Digital Convergence
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• v.15 no.4
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• pp.549-554
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• 2017

This study conducted a survey on 319 Chinese women in their 20s to 50s living in three large cities in China, with an aim to analyze the influence on the purchasing behavior and satisfaction for Korean cosmetics depending on their complex purchasing tendencies. According to the research, the rational tendency was higher when the subjects were over 40 years old and married, and the impulsive tendency was the highest in those in their 30s. There was no huge difference in regions depending on the two tendencies, while there were statistically significant differences in purchasing period, times and costs when buying cosmetics. In addition, purchasing satisfaction for cosmetics had a positive correlation with purchasing tendencies. The subjects pursued convenience in purchasing as their rational tendency was higher, while they sought the trends as their impulsive tendency was higher. Based on the results, it is expected to maximize purchasing satisfaction of Chinese female consumers depending on their purchasing tendencies, if the Korean cosmetics makers provide reliable quality assurance, product exchange and customer management services. It is also expected to help revitalize the beauty market for China as well as Southeast Asia, if the Korean cosmetics companies implement differentiated marketing strategies targeting the customers in the age group with the impulsive consumption tendency.

• The Journal of Society for e-Business Studies
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• v.15 no.1
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• pp.39-60
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• 2010

It becomes common thing that many customers buy the goods through the online shopping mall as internet grows very fast. The information cascades that happen when a person imitates the other's acts also it occurs in online. Many people buy the goods referring on other people's purchasing experiences and such cases are spreading more and more. Through numerous existing researches, the researches in association with this issue have been studied on the information cascades effect on offline or online separately. The research of comparing the information cascades effects from the offline word of mouth (WOM) and the online review has not studied yet. On that reason this study shows that the online review induces the information cascades. We also compared the effects with information cascades effects from traditional offline word of mouth. In result of this study, the following points have been concluded. Firstly, we examined that information cascades was occurred through both the online review and offline word of mouth. Secondly, the information cascades effect through the online review is greater than through the offline words of mouth. It means the company has to understand the importance of the online review and manage it. Thirdly, the information cascades effects are occurred differently in accordance with the goods brands. Therefore a company has to know whether its products is superior to the competitor's one or not.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.475-480
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• 2005

인터넷상에 존재하는 수 많은 웹 페이지들에는 정형화되지 않은 각종 정보들이 이종의 형태로 산재되어 있다. 현재의 검색 기술을 통하여 필요한 정보를 찾아내는 것은 시간과 비용이 많이 소요되는 비효율적인 방법으로 이뤄지고 있다. 이러한 상황에서 사용자가 원하는 정보를 검색 및 추출해내어 정형화시키는 것은 매우 중요하다. 전자상거래의 폭발적 성장에도 불구하고 전자상거래 표준 활용 및 적용이 미비하여 e- Procurement, e-Marketplace, on-Line Shopping Mall 등에서 소비자가 원하는 상품 정보를 손쉽게 획득하지 못하고 있다. 이는 공급자에게는 보다 많은 매출의 기회를 구매자에게는 보다 좋은 자재 및 상품을 저렴한 가격에 소싱 할 수 있는 기회를 제공하지 못하는 문제점이 발생한다. 본 연구에서 제안하고자 하는 지능형 상품 에이전트는 소비자가 구매하고자 하는 특정 상품에 대한 공급자 검색 문제를 해결하기 위하여, 시스템 내부 정보의 확장 및 지식화 뿐만 아니라 웹 상의 다양한 상품 정보를 자동적으로 수집 및 가공하여 저장하는 역할을 수행한다. 이러한 연구를 위해서 사용한 기술은 우선 database 의 schema 를 읽어 들일 수 있는 DB schema reader, 인터넷 웹 페이지(웹문서)를 방문해서 다양한 정보들의 URL을 수집하는 일을 하는 Meta Search Engine 과 Focused Crawler, 그리고 다른 형태의 데이터 구조를 특정 목적에 따라 표준화된 형태로 바꾸는 Wrapper가 있다. 이러한 기술들을 연동하여 필요한 정보들을 추출 공급자 검색 문제를 해결하고자 하는 것이 연구의 목적이다. 정보추출은 사용자의 관심사에 적합한 문서들로부터 어떤 구체적인 사실이나 관계를 정확히 추출하는 작업을 가리킨다.앞으로 e-메일, 매신저, 전자결재, 지식관리시스템, 인터넷 방송 시스템의 기반 구조 역할을 할 수 있다. 현재 오픈웨어에 적용하기 위한 P2P 기반의 지능형 BPM(Business Process Management)에 관한 연구와 X인터넷 기술을 이용한 RIA (Rich Internet Application) 기반 웹인터페이스 연구를 진행하고 있다.태도와 유아의 창의성간에는 상관이 없는 것으로 나타났고, 일반 유아의 아버지 양육태도와 유아의 창의성간의 상관에서는 아버지 양육태도의 성취-비성취 요인에서와 창의성제목의 추상성요인에서 상관이 있는 것으로 나타났다. 따라서 창의성이 높은 아동의 아버지의 양육태도는 일반 유아의 아버지와 보다 더 애정적이며 자율성이 높지만 창의성이 높은 아동의 집단내에서 창의성에 특별한 영향을 더 미치는 아버지의 양육방식은 발견되지 않았다. 반면 일반 유아의 경우 아버지의 성취지향성이 낮을 때 자녀의 창의성을 향상시킬 수 있는 것으로 나타났다. 이상에서 자녀의 창의성을 향상시키는 중요한 양육차원은 애정성이나 비성취지향성으로 나타나고 있어 정서적인 측면의 지원인 것으로 밝혀졌다.징에서 나타나는 AD-SR맥락의 반성적 탐구가 자주 나타났다. 반성적 탐구 척도 두 그룹을 비교 했을 때 CON 상호작용의 특징이 낮게 나타나는 N그룹이 양적으로 그리고 내용적으로 더 의미 있는 반성적 탐구를 했다용을 지원하는 홈페이지를 만들어 자료 제공 사이트에 대한 메타 자료를 데이터베이스화했으며 이를 통해 학생들이 원하는 실시간 자료를 검색하여 찾을 수 있고 홈페이지를 방분했을 때 이해하기 어려운 그래프나 각 홈페이지가 제공하는 자료들에 대한 처리 방법을 도움말로 제공받을 수 있게 했다. 실시간 자료들을 이용한 학습은 학생들의 학습 의욕과 탐구 능력을 향상시켰으

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3597-3609
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• 2012

Purpose: This study was done to develop the multidimensional scale of addictive behavior for adolescents. Methods: The process involved construction of a conceptual framework, initial items, verification of content validity, selection of secondary items, and extraction of final items. The participants were 636 adolescents in six middle schools and four high schools. Results: Seventy items were selected for the final scale, and categorized 8 factors explaining 56.5% of total variance. The factors were labeled as game addictive behavior, shopping addictive behavior, mobile phone addictive behavior, nicotine addictive behavior, television addictive behavior, gambling addictive behavior, alcohol addictive behavior, and internet addictive behavior. The scores for the scale were significantly correlated with addictive personality and self-control. Cronbach's alpha coefficient for the 70 items was .94. Scale scores identified adolescents as addictive behavior group, risk group, and average group. Conclusion: The above findings indicate that the multidimensional scale of addictive behavior for adolescents has good validity and reliability when used with adolescents. More importantly, it provides the first step toward developing a addiction prevention program. Additionally the scales provide an education or guideline, and proper physical and mental health management of youth in research and practice for the promotion of education.

• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.525-543
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• 2008

Recently, the scope of user interface is increasing the relative importance in software development dramatically. As a result, there are various relative technologies like as SWING, MFC, Web 2.0, and etc. However, most current software developments are progressed in separate development process with user interface part and business part respectively. This causes the problems, like as a difficulty in the integration process, an development period's delay, and a poor reusability for the constructed models. That is, the extendability and reusability of the created models is being decreased because UI modeling is not systematic and hierarchical, and the consistent integration technique between UI modeling and business modeling does not supported. To solve these problems, this paper proposes an unified and systematic UI modeling process based on UML, using the hierarchical metamodel according to the abstraction levels of development phase. We suggest an UI metamodel, which contains a hierarchy by layering the modeling elements in PIM and PSM based on maturity degree of the development. An hierarchical modeling process combined UI modeling and business modeling is built by applying the UI and business metamodel in terms of three modeling phases(concept/specification/concrete). The effectiveness of the modeling process is shown by applying the proposed process into an Internet Shopping Mall System. Through the exploratory results, the hierarchical UI metamodel and process can produce systematic and layered UI models. This can improve the quality and reusability of models.

• The Journal of Korean society of community based occupational therapy
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• v.8 no.3
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• pp.13-23
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• 2018

Objective : This study was conducted to investigate the leisure activities and self-efficacy according to sensory processing feature of university students. Methods : The survey was conducted from March to June, 2018. A total of 235 university students in Jeolla and Gyeongsang area participated. We used Adolescent/Adult Sensory Profiles to investigate sensory processing feature, Leisure Activity Questionnaires to examine leisure activities, and Self-Efficacy Scale for self-efficacy. This study identified the frequency of leisure activities of university students, the frequency of leisure activities and self-efficiency according to the sensory processing feature, and the leisure activities according to the feature of sensory seeking. Results : For the frequency of leisure activities and self-efficacy according to sensory processing feature of university students, only sensory seeking showed significantly difference in the leisure activity frequency, and the self-efficacy was significantly difference according to the feature of all types of sensory processing (p<.05). In addition, this study identified that leisure activities according to the feature of sensory seeking showed a significantly difference in gym, watching TV, shopping, internet search and web surfing (p<.05, p<.01). Conclusion : According to sensory seeking feature of university students, leisure activities and self-efficacy showed a significant difference. In order to encourage leisure activities of university students and to improve their self-efficacy, an interventional approach based on an understanding of sensory processing characteristics will be needed.