• Asia pacific journal of information systems
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• 제14권2호
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• pp.131-149
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• 2004

Collaborative filtering is one of popular techniques for personalized recommendation in e-commerce sites. An advantage of collaborative filtering is that the technique can work with sparse evaluation data to predict preference scores of new alternative contents or advertisements. There is, however, no in-depth study about the sparsity effect of customer's evaluation data to the performance of recommendation. In this study, we investigate the sparsity effect and hybrid usages of customers' evaluation data and purchase data using an experiment result. The result of the analysis shows that the performance of recommendation decreases monotonically as the sparsity increases, and also the hybrid usage of two different types of data; customers' evaluation data and purchase data helps to increase the performance of recommendation in sparsity situation.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.1266-1269
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• 2003

Many studies have indicated that most of a product's cost is fixed early in its lift cycle, before the original design cycle is complete. This implies that we should consider various aspects of product lift cycle at the design stage. This means the need of collaboration in design stage. Because the Internet provides instant access to a wealth of design information, the Internet is used by the collaborative design team members as a medium to share data, information and knowledge, and in some cases for product data management and project management by integrating the Web with appropriate technologies. This paper presents a real-time collaborative design system for powerful interaction performance, based on the Internet and Web technologies. Using The system use the client/server architecture and the purpose of the system is to provide a method that enables real-time view, review and modification of the 3D model through the Internet.

• 산업공학
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• 제19권1호
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• pp.70-77
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• 2006

One of the problems in developing a collaborative recommendation system is the scalability. To alleviate the scalability problem efficiently, enhancing the performance of the recommendation system, we propose a new recommendation system using feature selection. In our experiments, the proposed system using about a third of all features shows the comparable performances when compared with using all features in light of precision, recall and number of computations, as the number of users and products increases.

• 한국컴퓨터정보학회논문지
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• 제17권4호
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• pp.83-90
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• 2012

대규모의 상품을 다루는 전자상거래 시스템에서 개인화된 추천은 필수적인 기능이 되고 있다. 대표적 추천 알고리즘인 협업필터링은 내용기반 추천에 비하여 뛰어난 추천성능을 제공해 주고 있으나, 희박성, 신규 아이템 문제(Cold-start), 확장성 등의 근본적인 한계를 갖고 있다. 본 연구에서는 추가적으로 협업필터링이 목표 대상자에 따라 비일관된 예측 능력의 차이를 보이는 추천 성능의 편차 문제를 제기하고자 한다. 추천성능의 편차는 기존의 Mean Absolute Error(MAE)에 의해서는 측정되기 어려우며 또한 정확도, 재현율 지표와도 독립적으로 평가되고 있다. 협업알고리즘의 정확한 성능평가를 위해서 본 연구에서는 MAE, MAE 편차, 정확도, 재현율을 포괄적으로 평가할 수 있는 확장 성능평가모델을 제안하고 이를 클러스터링 기반 협업필터링에 적용하여 성능을 비교 분석한다.

• Journal of Information Technology Applications and Management
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• 제29권6호
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• pp.81-93
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• 2022

As deep learning technology in natural language and visual processing has rapidly developed, collaborative filtering-based recommendation systems using deep learning technology are being actively introduced in the recommendation field. In this study, OCF-GAN, a hybrid collaborative filtering model using GAN, was proposed to solve the one-class and cold-start problems, and its usefulness was verified through performance evaluation. OCF-GAN based on conditional GAN consists of a generator that generates a pattern similar to the actual user preference pattern and a discriminator that tries to distinguish the actual preference pattern from the generated preference pattern. When the training is completed, user preference vectors are generated based on the actual distribution of preferred items. In addition, the cold-start problem was solved by using a hybrid collaborative filtering recommendation method that additionally utilizes user and item profiles. As a result of the performance evaluation, it was found that the performance of the OCF-GAN with additional information was superior in all indicators of the Top 5 and Top 20 recommendations compared to the existing GAN-based recommender. This phenomenon was more clearly revealed in experiments with cold-start users and items.

• 한국ITS학회:학술대회논문집
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• 한국ITS학회 2010년도 춘계학술대회
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• pp.18-21
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• 2010

• Journal of Information Processing Systems
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• 제9권1호
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• pp.157-172
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• 2013

There are many recommendation systems available to provide users with personalized services. Among them, the most frequently used in electronic commerce is 'collaborative filtering', which is a technique that provides a process of filtering customer information for the preparation of profiles and making recommendations of products that are expected to be preferred by other users, based on such information profiles. Collaborative filtering systems, however, have in their nature both technical issues such as sparsity, scalability, and transparency, as well as security issues in the collection of the information that becomes the basis for preparation of the profiles. In this paper, we suggest a movie recommendation system, based on the selection of optimal personal propensity variables and the utilization of a secure collaborating filtering system, in order to provide a solution to such sparsity and scalability issues. At the same time, we adopt 'push attack' principles to deal with the security vulnerability of collaborative filtering systems. Furthermore, we assess the system's applicability by using the open database MovieLens, and present a personal propensity framework for improvement in the performance of recommender systems. We successfully come up with a movie recommendation system through the selection of optimal personalization factors and the embodiment of a safe collaborative filtering system.

• 창의정보문화연구
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• 제4권3호
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• pp.221-230
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• 2018

추천 시스템의 주요 방법인 협력 필터링 기술은 실제 상업용 온라인 시스템에서 성공적으로 구현되어 서비스가 제공되고 있다. 그러나, 이 기술은 본질적으로 여러 가지 단점을 내포하는데, 데이터 희소성, 콜드 스타트, 확장성 문제 등이 그 예이다. 확장성 문제를 해결하기 위하여 클러스터링 기법을 활용한 협력 필터링 방법이 연구되어 왔다. 본 연구에서 제안하는 협력 필터링 시스템에서는 가장 널리 활용되는 클러스터링 기법들 중 하나인 K-means 알고리즘의 단점을 개선하고자 유전자 알고리즘을 이용한다. 또한, 기존 연구에서 최적화된 클러스터링 결과를 추구하였던 것과는 달리, 제안 방법은 클러스터링 결과를 활용한 협력 필터링 시스템 성능의 최적화를 목표로 하므로, 실질적으로 시스템의 성능을 향상시킬 수 있다.

• 수산해양교육연구
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• 제26권2호
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• pp.284-295
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• 2014

The purpose of the study was to validate the components of practical collaborative competencies by analyzing the perceptions of corporate personnel on practical collaborative competencies. The study reviewed the theories of collaborative intelligence, collective intelligence, cooperative learning, and learning communities. Based on the results of the literature review, the study derived seven categories of participative motivation for group activities, ability to share thinking and consciousness, motivation to share experiences, ability to control emotion, ability to promote interaction, creativity, and collaborative performance as the core competencies. To validate the elements, survey was conducted for 186 corporate personnels. The results showed that the personnels perceived the following elements as important collaborative competencies: participative motivation for group activities, motivation to form participatory atmosphere, ability to manage conflict effectively, ability to form relationships, ability to form positive team atmosphere.

• Nano
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• 제13권11호
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• pp.1850130.1-1850130.12
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• 2018

A novel strontium titanate/binary metal sulfide ($SrTiO_3/SnCoS_4$) heterostructure was synthesized by a simple two-step hydrothermal method. The visible-light-driven photocatalytic performance of $SrTiO_3/SnCoS_4$ composites was evaluated in the degradation of methyl orange (MO) under visible light irradiation. The photocatalytic performance of $SrTiO_3/SnCoS_4-5%$ is much higher than that of pure $SrTiO_3$, $SnCoS_4$, $SrTiO_3/SnS_2$ and $SrTiO_3/CoS_2$. The $SrTiO_3/SnCoS_4$ composite material with 5 wt.% of $SnCoS_4$ showed the highest photocatalytic efficiency for MO degradation, and the degradation rate could reach 95% after 140 min irradiation time. The enhanced photocatalytic activity was ascribed to not only the improvement of visible light absorption efficiency, but also the construction of a heterostructure which make it possible to effectively separate photoexcited electrons and holes in the two-phase interface.