• IE interfaces
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• v.19 no.1
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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.

• Journal of Physiology & Pathology in Korean Medicine
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• v.28 no.4
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• pp.446-451
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• 2014

The purpose of this study was to investigate different attitudes of officers depending on system of collaborative practice between traditional Korean medicine and western medicine. A total of 103 officials were surveyed using structured questionnaires. Data were analyzed using descriptive statistics, ${\chi}^2$ test with the SPSS program. Use of oriental medicine clinic was significantly higher and use of general hospitals was significantly lower in a group of users (p=.021). Higher rates of disease status were found in a group of users (p=.024). 'Overcome limits of Traditional Korean Medicine and Western Medicine' and 'collaborative practice would bring benefits' as the reasons of using collaborative practice between Traditional Korean Medicine and Western Medicine showed higher rates (p<.001). It showed high interests in collaborative practice between Traditional Korean Medicine and Western Medicine in two groups, but higher rates of prospect of collaborative practice between Traditional Korean Medicine and Western Medicine revitalization were found in the group of users. Also, more than 60% of the officers showed positive attitudes in the system of the collaborative practice. Therefore, correct researches on actual conditions about collaborative practice between Korean and Western Medicine and positive and negative aspects of this collaborative practice pointed by candidates need to be considered in order to improve candidates' health condition.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1062-1072
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• 2004

Collaborative filtering systems based on ｛user-document｝ matrix are effective in recommending web documents to user. But they have a shortcoming of decreasing the accuracy of recommendations by the first rater problem and the sparsity. This paper proposes the automatic preference rating method that generates user profile to solve the shortcoming. The profile in this paper is content-based collaborative user profile. The content-based collaborative user profile is generated by combining a content-based user profile with a collaborative user profile by mutual information method. Collaborative user profile is based on ｛user-document｝ matrix in collaborative filtering system, thus, content-based user profile is generated by relevance feedback in content-based filtering systems. After normalizing combined content-based collaborative user profiles, it automatically rates user preference by reflecting normalized profile in ｛user-document｝matrix of collaborative filtering systems. We evaluated our method on a large database of user ratings for web document and it was certified that was more efficient than existent methods.

• Journal of Service Research and Studies
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• v.6 no.4
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• pp.47-57
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• 2016

Open source has an amazing spread with the advent of smartphones. Open-source Moodle in e-learning areas are free of LMS (Learning Management System) and the most widely used worldwide, except for the black board commercial programs. One reason is well designed to support collaborative learning and interaction based on constructivist principles, which is the core principle of e-learning in particular that the theoretical basis of educational technology has a high educational effectiveness and benefits. This study examines the operational practices of collaborative learning using open source learning management system Moodle program. It introduces specific information to support the user of the collaborative learning. It looks at the advantages and singularity of collaborative learning in e-learning through examples shown. The purpose of this study is the importance of the relationship between learners and the importance of self-learning of collaborative learning through collaborative learning in a knowledge repository of Moodle. In addition, collaborative learning outcomes are is based on the motivation of learners and playfulness.

• Journal of Ginseng Research
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• v.41 no.3
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• pp.373-378
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• 2017

Ocotillol-type saponins are one kind of tetracyclic triterpenoids, sharing a tetrahydrofuran ring. Natural ocotillol-type saponins have been discovered in Panax quinquefolius L., Panax japonicus, Hana mina, and Vietnamese ginseng. In recent years, the semisynthesis of 20(S/R)-ocotillol-type saponins has been reported. The biological activities of ocotillol-type saponins include neuroprotective effect, antimyocardial ischemia, antiinflammatory, antibacterial, and antitumor activities. Owing to their chemical structure, pharmacological actions, and the stereoselective activity on antimyocardial ischemia, ocotillol-type saponins are subjected to extensive consideration. In this review, we sum up the discovery, semisynthesis, biological activities, and metabolism of ocotillol-type saponins.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.101-115
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• 2008

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.

• Journal of Information Processing Systems
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• v.4 no.3
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• pp.103-112
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• 2008

This paper proposes a policy adjuster-driven Grid workflow management system for collaborative healthcare platform, which supports collaborative heart disease diagnosis applications. To select policies according to service level agreement of users and dynamic resource status, we devised a policy adjuster to handle workflow management polices and resource management policies using policy decision scheme. We implemented this new architecture with workflow management functions based on policy quorum based resource management system for providing poincare geometrycharacterized ECG analysis and virtual heart simulation service. To evaluate our proposed system, we executed a heart disease identification application in our system and compared the performance to that of the general workflow system and PQRM system under different types of SLA.

• Journal of Creative Information Culture
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• v.4 no.3
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• pp.221-230
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• 2018

Collaborative filtering technique is a major method of recommender systems and has been successfully implemented and serviced in real commercial online systems. However, this technique has several inherent drawbacks, such as data sparsity, cold-start, and scalability problem. Clustering-based collaborative filtering has been studied in order to handle scalability problem. This study suggests a collaborative filtering system which utilizes genetic algorithms to improve shortcomings of K-means algorithm, one of the widely used clustering techniques. Moreover, different from the previous studies that have targeted for optimized clustering results, the proposed method targets the optimization of performance of the collaborative filtering system using the clustering results, which practically can enhance the system performance.

• Journal of the Korea Society of Computer and Information
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• v.23 no.7
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• pp.11-17
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• 2018

In this paper, we propose how to improve the lack of diversity in collaborative filtering, using tag scores contained in items rather than ratings of items. Collaborative filtering has excellent performance among recommendation system, but it is evaluated as lacking diversity. In order to solve this problem, this paper proposes a method for supplementing diversity lacking in collaborative filtering by using tags. By using tags that can be used universally without using the characteristics of specific articles in a recommendation system, The proposed method can be used.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.159-162
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• 1997

Since customer's demand is various and product life cycle is getting shorter, many manufacturing company is trying to reduce product development time and cost. For that reason they make an effort to design product on collaborative environment. The various activities in a product development are highly distributed. This distributed nature of the activities implies that teams will be working indifferent place and technical environments. Thus at a given time, teams might work on he same product from different perspectives. This will require efficient communication amongst the various individuals and the various softwaretools that are used by them. Therefore, there is a need for a computerized frame work that can support distributed design such that participants from different backgrounds collaborate towards one common goal. This paper presents the architecture of a collaborative design system. It then reports on the study of computerized frame work focused on collaboration for product development.