• International journal of advanced smart convergence
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• v.9 no.2
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• pp.1-7
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• 2020

As the demand for health screening increases, there is a need for efficient design of screening items. We build machine learning models for health screening and recommend screening items to provide personalized health care service. When offline, a synthetic data set is generated based on guidelines and clinical results from institutions, and a machine learning model for each screening item is generated. When online, the recommendation server provides a recommendation list of screening items in real time using the customer's health condition and machine learning models. As a result of the performance analysis, the accuracy of the learning model was close to 100%, and server response time was less than 1 second to serve 1,000 users simultaneously. This paper provides an adaptive and automatic recommendation in response to changes in the new screening environment.

• Journal of Digital Convergence
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• v.11 no.8
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• pp.213-218
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• 2013

In this paper, when vehicle inspection is made, the check way is recommended based on the intelligent and personalized in the workplace, education, and other space-time according to the current situation. These results increase productivity, reduce costs, and improve performance. So we designed vehicle inspection recommendation system using ontology. Recommendation method is that components connected concept are shown according to weight value. if components are connected with other concept, the components are extended.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.147-156
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• 2003

Collaborative Filtering is a popular technology in electronic commerce, which adapt the opinions of entire communities to provide interesting products or personalized resources and items. It has been applied to many kinds of electronic commerce domain since Collaborative Filtering has proven an accurate and reliable tool. But educational application remain limited yet. We design collaborative filtering recommendation system using user's ratings in educational contents recommendation. Also We propose a method of similarity compensation using user's information for improvement of recommendation accuracy. The proposed method is more efficient than the traditional collaborative filtering method by experimental comparisons of mean absolute error(MAE) and reciever operating characteristics(ROC) values.

• The Journal of Information Systems
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• v.27 no.4
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• pp.71-96
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• 2018

Purpose Recently, social interest in the convergence research is at its peak. However, contrary to the keen interest in convergence research, an infrastructure that makes it easier to recruit researchers from other fields is not yet well established, which is why researchers are having considerable difficulty in carrying out real convergence research. In this study, we implemented a researcher recommendation system that helps researchers who want to collaborate easily recruit researchers from other fields, and we expect it to serve as a springboard for growth in the convergence research field. Design/methodology/approach In this study, we implemented a system that recommends proper researchers when users enter keyword in the field of research that they want to collaborate using word embedding techniques, word2vec. In addition, we also implemented function of keyword suggestions by using keywords drawn from LDA Topicmodeling Algorithm. Finally, the UI of the researcher recommendation system was completed by utilizing the collaborative messenger Slack to facilitate immediate exchange of information with the recommended researchers and to accommodate various applications for collaboration. Findings In this study, we validated the completed researcher recommendation system by ensuring that the list of researchers recommended by entering a specific keyword is accurate and that words learned as a similar word with a particular researcher match the researcher's field of research. The results showed 85.89% accuracy in the former, and in the latter case, mostly, the words drawn as similar words were found to match the researcher's field of research, leading to excellent performance of the researcher recommendation system.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1346-1357
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• 2021

The drone technology, which is receiving a lot of attention due to the 4th industrial revolution, requires an Unmanned Aerial Vehicles'(UAVs) flight path search algorithm for automatic operation and driver assistance. Various studies related to flight path prediction and recommendation algorithms are being actively conducted, and many studies using the A-Star algorithm are typically performed. In this paper, we propose an Optimal 3D Flight Path Recommendation System for unmanned aerial vehicles. The proposed system was implemented and simulated in Unity 3D, and by indicating the meaning of the route using three different colors, such as planned route, the recommended route, and the current route were compared each other. And obstacle response experiments were conducted to cope with bad weather. It is expected that the proposed system will provide an improved user experience compared to the existing system through accurate and real-time adaptive path prediction in a 3D mixed reality environment.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.93-104
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• 2023

In modern society, the service method is tended to prefer the non-face-to-face method rather than the face-to-face method. However, services that recommend products such as shoes will inevitably be face-to-face method. In this paper, for the purpose of non-face-to-face service, a system that a foot size is automatically measured and some shoes are recommended based on the measurement result is proposed. To analyze the performance of the proposed method, size measurement error rate and recommendation performance were analyzed. In the recommendation performance experiments, a total of 10 methods for similarity calculation were used and the recommendation method with the best performance among them was applied to the system. From the experiments, the error rate the foot size was small and the recommendation performance was possible to derive significant results. The proposed method is at the laboratory level and needs to be expanded and applied to the real environment. Also, the recommendation method considering design could be needed in the future work.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.1027-1038
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• 2006

There are many technical problems in the recommendation system based on very large database(VLDB). So, it is necessary to study the recommendation system' structure and the data-mining technique suitable for the large scale Internet shopping mail. Thus we design and implement the product recommendation system using k-means clustering algorithm and sequential pattern technique which can be used in large scale Internet shopping mall. This paper processes user information by batch processing, defines the various categories by hierarchical structure, and uses a sequential pattern mining technique for the search engine. For predictive modeling and experiment, we use the real data(user's interest and preference of given category) extracted from log file of the major Internet shopping mall in Korea during 30 days. And we define PRP(Predictive Recommend Precision), PRR(Predictive Recommend Recall), and PF1(Predictive Factor One-measure) for evaluation. In the result of experiments, the best recommendation time and the best learning time of our system are much as O(N) and the values of measures are very excellent.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.49-55
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• 2019

In this paper, we propose ontology-based recommendation system for supporting maintenance of Korean architectural heritage. This study includes the following: 1) design of ontology expressing repair information of architectural heritage, 2) creation of repair case DB, 3) creation of a recommendation system of repair method. For this study, we designed the ontology that expresses the information of Korean wooden building cultural heritage by referring to the existing heritage ontologies. Second, we created the repair information database based on the repair contents and the expert interview data provided by the National Institute of Cultural Heritage and the Cultural Heritage Administration. Third, we developed a system that recommends the repair method of Korean wooden architectural heritage with the most similar phenomena and causes. This study contributes to sharing repair knowledge and determining repair methods for architectural heritage repair.

• The Journal of the Korea Contents Association
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• v.19 no.10
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• pp.353-363
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• 2019

This study is for the use of color recommendation system for the color combination of mobile application. For this study, color combination methods of a material design color system that recommends harmonized colors automatically and of a mobile web application were applied to a mobile application design and a color combination experiment was carried out. Then for a survey on the experiment using the two methods, color combinations, selected colors and satisfaction with outputs were investigated on a 7-point Likert scale. And color combination characteristics of outputs were compared. It was found that the material design color palette made it easy to select colors by systematizing the regular coloring stages of fixed colors automatically, but there were differences in color compositions and color scopes of dominant color, assort color and accent colors, which are three-color combinations of mobile web application and accent color selection function was required for each design, since only primary colors and secondary colors could be selected. Moreover, chromatic colors were used a lot in the material system because of the fixed color scopes and color combination scopes and images of color combination outcomes varied depending on the color combination scopes, even when tones with a big contrast or complementary colors were selected. The role of color composition was important according to the color combination scopes.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.682-685
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• 2002

In this paper, we defined necessary operations and functional blocks of a multiplexer for 3-D video systems and present our multiplexer design. We adopted the ITU-T's recommendation(H.222.0) to define the operations and functions of the multiplexer and explained the data structures and details of the design for multiview image processing. The data structure of TS(Transport Stream) and PES (Packetized Elementary Stream) in ITU-T Recommendation H.222.0 does not fit our multiview image processing system, because this recommendation is fur wide scope of transmission of non-telephone signals. Therefore, we modified these TS and PES stream structures. The TS is modified to DSS(3D System Stream) and PES is modified to SPDU(DSS Program Data Unit). We constructed the multiplexer through these modified DSS and SPDU. The number of multiview image channels is nine, and the image class employed is MPEG-2 SD(Standard Definition) level which requires a bandwidth of 2∼6 Mbps. The required clock speed should be faster than 54(= 6 ${\times}$ 9)㎒ which is the outer interface clock speed. The inside part of the multiplexer requires a clock speed of only 1/8 of 54㎒, since the inside part of the multiplexer operates by the unit of byte. we used ALTERA Quartus II and the FPGA verification for the simulation.