• 지능정보연구
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• 제8권2호
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• pp.91-103
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• 2002

기존의 인터넷 웹사이트에서는 사용자의 만족을 극대화시키기 위하여 사용자별로 개인화 된 서비스를 제공하는 협력적 필터링 방식을 적용하고 있다. 협력적 여과 기술은 비슷한 선호도를 가지는 사용자들과의 상관관계를 기반으로 취향에 맞는 아이템을 예측하여 특정 사용자에게 추천하여준다. 그러나 협력적 필터링은 추천을 받기 위해서 특정 수 이상의 아이템에 대한 평가를 요구하며, 또한 전체 사용자에 대해 단지 비슷한 선호도를 가지는 일부 사용자 정보에 의지하여 추천함으로써 나머지 사용자 정보를 무시하는 경향이 있다. 그러나 나머지 사용자 정보에도 추천을 위한 유용한 정보가 숨겨져 있다. 우리는 이러한 숨겨진 유용한 추천 정보를 발견하기 위하여 본 논문에서는 협력적 여과 방식과 함께 데이터 마이닝(Data Mining)에서 사용되는 연관 규칙(Association Rule)을 추천에 사용한다. 연관 규칙은 한 항목 그룹과 다른 항목 그룹 사이에 존재하는 연관성을 규칙(Rule)의 형태로 표현한 것이다. 이와 같이 생성된 연관 규칙은 개인 구매도 분석, 상품의 교차 매매(Cross-Marketing), 카탈로그 디자인, 염가 매출품(Loss Leader)분석, 상품 진열, 구매 성향에 따른 고객 분류 다양하게 사용되고 있다. 그러나 이런 연관 규칙은 추천 시스템에서 잘 응용되지 못하고 있는 실정이다. 본 논문에서 우리는 연관 규칙을 추천 시스템에 적용해, 항목그룹 사이에 연관성을 유도함으로써 추천에 효율적으로 사용할 수 있음을 보였다 즉 전체 사용자의 히스토리(History) 정보를 기반으로 아이템 사이의 연관 규칙을 유도하고 협력적 여과 방식과 함께 보조적으로 연관 규칙을 추천을 위해 사용함으로써 추천 시스템에 효율성을 높였다.

• 한국정밀공학회지
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• 제20권9호
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• pp.27-31
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• 2003

• 한국실내디자인학회논문집
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• 제22호
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• pp.132-138
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• 2000

Internet services are utilizing a variety of server/client technologies. In particular internet technologies provide improved accessibility to information for facility management customers and users for the systems. This study is the architectural data exchange system development more effective management and accept using on Internet web environment. This paper is the explore the use of computers in architectural planning that how the information may be extracted drawing entered into database and exchanged architectural detail data interfaces. System support communication and interactive collaboration among designers through complex Building object during the Design. There are four part in collaborative design system. User Management system, Standard Database System, Project Database System and Interface system. All Data are recognizable format include drawing file and contents. Web/DB server supported communication and collaboration among partners in the building design and construction process. Collaborative Design system is provide new conceptual framework that exist in the Web.

• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.441-450
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• 2003

Collaborative filtering is one of the most widely used methodologies for recommendation system. Collaborative filtering is based on a data matrix of each customer's preferences and frequently, there exits missing data problem. We introduced two imputation approach (multiple imputation via Markov Chain Monte Carlo method and multiple imputation via bootstrap method) to improve the prediction performance of collaborative filtering and evaluated the performance using EachMovie data.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2020년도 제62차 하계학술대회논문집 28권2호
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• pp.385-386
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• 2020

In this paper, we propose a collaborative filtering recommendation algorithm based on the LDA2Vec topic model. By extracting and analyzing the article's content, calculate their semantic similarity then combine the traditional collaborative filtering algorithm to recommend. This approach may promote the system's recommend accuracy.

• 복식문화연구
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• 제19권3호
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• pp.531-541
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• 2011

This study suggests basic data for the standardization of school uniform purchase by examining the statistics of purchasing practice school uniforms from information sources, purchasing methods, and consumer' perception about collaborative purchases. A survey was conducted with first grade male and female middle-school students, and their parents. A total of 344 questionnaires were returned and analyzed. The results were as follows: first, when making purchases, information sources were explained by parents, friends, senior students, or workers at uniform shops. The purchasing methods were popular brand uniforms or specialized uniform shops. Second, four factors were extracted from purchasing data for factor analysis. The factors were comfort, appearance, service, other external factors, and promotions. Third, the perception analysis and need of collaborative purchases were indicated by 90% of the students' parents, who were aware of collaborative purchase. Additionally, 71.2% answered collaborative purchase was necessary. Fourth, for future uniform purchases, 75.6% of the students answered to buy more popular brands, or products from specialized school uniform shops, while 54.4% of the parents answered positively to collaborative purchases. The results of the examination of consumer school uniform purchasing behavior will provide useful strategies for the standardization system for purchasing school uniforms.

• Journal of Computing Science and Engineering
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• 제7권1호
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• pp.21-29
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• 2013

The introduction of recommender systems to existing online services is now practically inevitable, with the increasing number of items and users on online services. Popular recommender systems have successfully implemented satisfactory systems, which are usually based on collaborative filtering. However, collaborative filtering-based recommenders suffer from well-known problems, such as popularity bias, and the cold-start problem. In this paper, we propose an innovative collaborative-filtering based recommender system, which uses the concepts of Experts and Novices to create fine-grained recommendations that focus on being novel, while being kept relevant. Experts and Novices are defined using pre-made clusters of similar items, and the distribution of users' ratings among these clusters. Thus, in order to generate recommendations, the experts are found dynamically depending on the seed items of the novice. The proposed recommender system was built using the MovieLens 1 M dataset, and evaluated with novelty metrics. Results show that the proposed system outperforms matrix factorization methods according to discovery-based novelty metrics, and can be a solution to popularity bias and the cold-start problem, while still retaining collaborative filtering.

• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2001년도 International Conference CALS/EC KOREA
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• pp.591-596
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• 2001

To deliver new products to market in a due time, companies often develop their products with numerous partners distributed around the world. Internet technologies can provide a cheap and efficient basis of collaborative product development among distributed partners. This paper provides a framework and its product database model that can support consistent product data during collaborative product development. This framework consists of four components for representing consistent product structure: the product configuration, assembly structure, multiple representations and engineering changes. A product database model realizing the framework is designed and implemented as a system that supports collaborative works in the areas of product design and technical publication. The system enables participating designers and technical publishers to complete their tasks with shared and consistent product data. It also manages the propagation of engineering changes among different representations for individual participants. The Web technologies introduced in this system enable participants to easily access and operate shared product data in a standardized and distributed computing environment.

• 공학교육연구
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• 제22권4호
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• pp.61-70
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• 2019

As product development process becomes complex, it becomes more important for engineering students to experience collaborative product development. Especially the collaboration experience based on Product Data Management (PDM) systems is useful, since participants are likely to use the same environment for their professional product development. However, instructors have difficulties to evaluate contribution of each participant to their projects during the practices, since it is hard to trace personal activities for collaborative design processes. To solve this problem, this study suggests a data-driven objective method that analyses product data accumulated in PDM databases to evaluate numerically calculated contributions of participants to their class projects. As a result, the quantitative measures provided by the data-driven analysis with qualitative measures for project results can improve the fairness and quality of evaluation of contributions of participants to collaborative projects. This study implemented the proposed evaluation method with an information system and discussed the result of the application of the system to product development practices.

• 한국정보시스템학회지:정보시스템연구
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• 제27권2호
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• pp.197-219
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• 2018

Purpose The purpose of this study is to examine what motivates users to adopt one of the emerging applications for collaborative consumption of sharing economy. Using the self-determination theory, motivation theory and TAM(Technology Acceptance Model) as the theoretical framework, this study illustrates important factors that influence adoption of collaborative consumption service. We develops the ICTs(Information and Communications Technologies) initiatives and motivation model to collaborative consumption. Design/methodology/approach This paper makes use of a quantitative methodology using survey questionnaire that allows for the measurement of the eight constructs(System Availability, Contents Quality, Design & Personalization, Security & Privacy, Emotional & Social Value, Economic Value, Attitude, Adoption & Consumption) contained in the hypothesized theoretical model on the basis of the prior literatures. Data collected from a sample of 227 respondents who have used the collaborative consumption services and provided the foundation for the examination of the proposed relationships in the model. Findings This study has the following implications for the users and providers of CC platforms and services. The ICTs initiatives (System Availability, Contents Quality, Design & Personalization, Security & Privacy) are the influential factors that motivate the emotional and social value to CC. On the other hand, The ICTs initiatives (System Availability, Contents Quality) are not very significant factors of economic value to CC. The empirical analysis result indicate that there are significant causal effect among emotional & social value, economic value, and adoption to CC. This study provides important theoretical implications for innovation adoption research through an empirical examination of the relationship between ICTs initiatives, motivation factors to collaborative consumption in the sharing economy.