• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.91-103
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• 2002

A collaborative filtering which supports personalized services of users has been common use in existing web sites for increasing the satisfaction of users. A collaborative filtering is demanded that items are estimated more than specified number. Besides, it tends to ignore information of other users as recommending them on the basis of information of partial users who have similar inclination. However, there are valuable hidden information into other users' one. In this paper, we use Association Rule, which is common wide use in Data Mining, with collaborative filtering for the purpose of discovering those information. In addition, this paper proved that Association Rule applied to Recommender System has a effects to recommend users by the relation between groups. In other words, Association Rule based on the history of all users is derived from. and the efficiency of Recommender System is improved by using Association Rule with collaborative filtering.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.9
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• pp.27-31
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• 2003

• Korean Institute of Interior Design Journal
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• no.22
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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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• v.14 no.3
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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.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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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.

• The Research Journal of the Costume Culture
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• v.19 no.3
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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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• v.7 no.1
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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.

• Proceedings of the CALSEC Conference
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• 2001.08a
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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.

• Journal of Engineering Education Research
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• v.22 no.4
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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.

• The Journal of Information Systems
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• v.27 no.2
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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.