• Journal of Mechanical Science and Technology
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• 제20권10호
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• pp.1534-1540
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• 2006

Concurrent Engineering (CE) is a popular method employed in product development. It treats the whole product design process by the consideration of product quality, cost, rate of progress, and demands of customers. The development of computer and network technologies provides a strong support to the realization of CE in practice. Aiming at the characteristics of CE and network collaborative design, this paper built network collaborative design system frame. Through the analysis of the network collaborative design modes based on CE, this paper provided a novel network collaborative design integration model. This model can integrate the product design information, design process, and knowledge. Intelligent collaboration was considered in the proposed model. The study showed that the proposed model considered main factors such as information, knowledge, and design process in collaborative design. It has potential application in CE fields.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 추계학술대회
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• pp.602-609
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• 2007

Combining collaborative filtering with some other technique is most common in hybrid recommender systems. As many recommended items from collaborative filtering seem to be similar with respect to content, the collaborative-content hybrid system suffers in terms of quality recommendation and recommending new items as well. To alleviate such problem, we have developed a novel method that uses a diversity metric to select the dissimilar items among the recommended items from collaborative filtering, which together with the input when fed into content space let us improve and include new items in the recommendation. We present experimental results on movielens dataset that shows how our approach performs better than simple content-based system and naive hybrid system

• 한국작물학회:학술대회논문집
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• 한국작물학회 2019년도 추계학술대회
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• pp.17-17
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• 2019

• 유통과학연구
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• 제16권2호
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• pp.19-24
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• 2018

Purpose - Drone delivery is expected to revolutionize the supply chain industry. This paper aims to introduce a collaborative parcel delivery problem by truck and drone (hereinafter called "TDRP") and propose a novel heuristic method to solve the problem. Research design, data, and methodology - To show the effectiveness of collaborative delivery by truck and drone, we generate a toy problem composed of 9 customers and the speed of drone is assumed to be two times faster than truck. We compared the delivery completion times by 'truck only' case and 'truck and drone' case by solving the optimization problem respectively. Results - We provide literature reviews for truck and drone routing problem for collaborative delivery and propose a novel and original heuristic method to solve the problem with numerical example. By numerical example, collaborative delivery is expected to reduce delivery completion time by 12~33% than 'truck only' case. Conclusions - In this paper, we introduce the TDRP in order for collaborative delivery to be effective and propose a novel and original heuristic method to solve the problem. The results of research will be help to develop effective heuristic solution and optimize the parcel delivery by using drone.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 ITC-CSCC -3
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• pp.1752-1755
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• 2002

The world wide web (WWW) already accounts f3r more Internee network traffic than any other application, including il and simple file transfer. It is also a collaborative technology in a weak sense of the word - it allows people to share information. Synchronous collaboration is where an interactive activity is simultaneous and in teal-time. Computer based real time collaborative systems like shared whiteboards. collaborative editor etc. are only beginning to emerge recently. These applications invoking more than two users exchanging information, require Multicast communication. Multicast communication is a transmission mode that is now supported by a variety of local and wide area networks. Multicasting enables multiparty communication across a wide area to sparsely distributed groups by minimizing the network load. Multicasting itself is one of the key technologies in the nut generation of the Internet This paper describes the technical issues from the aspect of multicast communication and its reliability in synchronous collaborative application.

• 경영과학
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• 제23권2호
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• pp.1-16
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• 2006

With the diffusion of the Internet, firms try to electronically collaborate with their partners in order to cut costs and gain profits. This, electronic Partnership, called 'Collaborative IT' is quite popular between large purchase enterprises and small-to-medium sized sub-contractors. This study investigates such relations. This study proposes three groups of research variables-interorganizational relationship, collaborative IT activity, and firm performance. the interorganizational relationship consists of trust, commitment, and asymmetry of commitment. Collaborative IT activity is composed of information sharing and workflow integration. The ultimate dependent variable is firm performance. It is hypothesized that the relationship factors influence the level of collaborative IT activity, while the latter in turn affects the firm performance. The relationship factors nay also directly affect the dependent variable. In addition, collaborative IT motive, as a moderating variable, may influence the causal relationship. By means of survey, ore hundred and eighty-two responses were obtained. Most sample companies are small-sized, in the manufacturing sector. The analysis of data reveals that both trust and commitment positively affects the level of collaborative IT activity, while asymmetry of commitment has negative effects. The workflow integration is significantly related with firm performance. Information sharing, however, has no signific3nt effects. Furthermore, asymmetry of commitment shows reverse relationship with firm performance. Collaborative IT motive works as a moderating variable between information sharing and firm performance. Finally, workflow integration is believed to mediate between relationship factors and firm performance.

• 한국도서관정보학회지
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• 제44권3호
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• pp.51-74
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• 2013

본 연구의 목적은 국내 공공도서관을 위한 공동보존서고 건립모형을 제안하는데 있다. 이를 위하여 공동보존서고 건립환경인 공공도서관 수장공간 부족률, 시도별 공동보존서고 건립의 우선순위, 수행해야 할 주요 기능과 업무, 바람직한 입지조건을 분석하였다. 이를 바탕으로 공동보존서고 건립의 기본원칙, 건축규모, 공공도서관의 이관자료 기준과 소유권 문제, 바람직한 관리운영 주체를 제시하였다. 따라서 정부와 모든 광역시도는 조속히 공동보존서고를 설립 운영해야 한다.

• 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.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2004년도 추계학술대회
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• pp.203-210
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• 2004

Due to the explosion of e-commerce, recommender systems are rapidly becoming a core tool to accelerate cross-selling and strengthen customer loyalty. There are two prevalent approaches for building recommender systems - content-based recommending and collaborative filtering. Collaborative filtering recommender systems have been very successful in both information filtering domains and e-commerce domains, and many researchers have presented variations of collaborative filtering to increase its performance. However, the current research on recommendation has paid little attention to the use of time related data in the recommendation process. Up to now there has not been any study on collaborative filtering to reflect changes in user interest. This paper proposes dynamic fuzzy clustering algorithm and apply it to collaborative filtering algorithm for dynamic recommendations. The proposed methodology detects changes in customer behavior using the customer data at different periods of time and improves the performance of recommendations using information on changes. The results of the evaluation experiment show the proposed model's improvement in making recommendations.