• Journal of KIISE
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• v.41 no.12
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• pp.1117-1125
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• 2014

Folksonomy data, which is derived from social tagging systems, is a useful source for understanding a user's intention and interest. Using the folksonomy data, it is possible to create an accurate user profile which can be utilized to build a personalized search system. However there are limitations in some of the traditional methods such as Vector Space Model(VSM) for user profiling and similarity computation. This paper suggests a novel method with graph-based user and document profile which uses the proximity information of query terms to improve personalized search. We demonstrate the performance of the suggested method by comparing its performance with several state-of-the-art VSM based personalization models in two different folksonomy datasets. The results show that the proposed model constantly outperforms the other state-of-the-art personalization models. Furthermore, the parameter sensitivity results show that the proposed model is parameter-free in that it is not affected by the idiosyncratic nature of datasets.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.80-89
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• 2009

The importance of personalized services has been attracted in smart home environments according to the development of ubiquitous computering. In this paper, we proposed the smart home personalized service system based on context information using the speech recognition. The proposed service consists of an OSGi framework based service mobile manager, service manager, voice recognition manager, and location manager. Also, this study defines the smart home space and configures the commands of units, sensor information, and user information that are largely used in the defined space as context information. In particular, this service identifies users who exist in the same space that shows a difficulty in the identification using RFID through the training model and pattern matching in voice recognition and supports the personalized service of smart home applications. In the results of the experiment, it was verified that the OSGi based automated and personalized service can be achieved through verifying users in the same space.

• Korean Journal of Community Nutrition
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• v.18 no.6
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• pp.565-576
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• 2013

The purpose of this study was to investigate the effects of nutrition education on nutrition knowledge, dietary attitude and dietary intake of Chinese college students in Korea. The subjects were 64 Chinese college students in Korea (educated group, 32 students vs. non-educated group, 32 students). Educated group was lessoned as group and/or individual. Nutrition education program consisted of four lessons (40min/lesson), '6 major nutrients & function (group lesson)', '6 food group and sources (group lesson)', 'personalized daily needed energy and food exchange units using Food Exchange System (individual lesson)', and 'smart choice of snacks and eating-out foods (group lesson)'. We examined the differences between educated group and non-educated group in nutrition knowledge, dietary attitudes and nutrients intake. After education, there were positive improvements on nutrition knowledge: 'function and foods of 6 nutrients', on dietary attitudes: 'type of breakfast' in educated group. In the evaluation of nutrient intakes according to Dietary Reference Intakes for Korean (KDRI), there were positive improvements on intake levels of riboflavin, fiber, vitamin B6, vitamin C, folate, Ca and K in the educated group. In the index of nutrition quality (INQ), nutrition adequacy ratio (NAR) and mean nutrition adequacy ratio (MAR) were significantly increased in the educated group. In conclusion, it is possible to improve nutrition knowledge, dietary attitude and dietary intake of Chinese college students in Korea through the nutrition education focused on personalized daily needed energy and food exchange units.

• Journal of Convergence for Information Technology
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• v.10 no.4
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• pp.1-10
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• 2020

The performance of the personalized product recommendation system for offline shopping malls is poor compared with the one using online environment information since it is difficult to obtain visitors' characteristic information. In this paper, a mobile robot platform is suggested capable of recommending personalized advertisement using customers' sex and age information provided by Face API of MS Azure Cloud service. The performance of the developed robot is verified through locomotion experiments, and the performance of API used for our robot is tested using sampled images from open Asian FAce Dataset (AFAD). The developed robot could be effective in marketing by providing personalized advertisements at offline shopping malls.

• Journal of Veterinary Science
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• v.22 no.3
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• pp.25.1-25.16
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• 2021

Background: Malignant lymphoma is the most common hematopoietic malignancy in dogs, and relapse is frequently seen despite aggressive initial treatment. In order for the treatment of these recurrent lymphomas in dogs to be effective, it is important to choose a personalized and sensitive anticancer agent. To provide a reliable tool for drug development and for personalized cancer therapy, it is critical to maintain key characteristics of the original tumor. Objectives: In this study, we established a model of hybrid tumor/stromal spheroids and investigated the association between canine lymphoma cell line (GL-1) and canine lymph node (LN)-derived stromal cells (SCs). Methods: A hybrid spheroid model consisting of GL-1 cells and LN-derived SC was created using ultra low attachment plate. The relationship between SCs and tumor cells (TCs) was investigated using a coculture system. Results: TCs cocultured with SCs were found to have significantly upregulated multidrug resistance genes, such as P-qp, MRP1, and BCRP, compared with TC monocultures. Additionally, it was revealed that coculture with SCs reduced doxorubicin-induced apoptosis and G2/M cell cycle arrest of GL-1 cells. Conclusions: SCs upregulated multidrug resistance genes in TCs and influenced apoptosis and the cell cycle of TCs in the presence of anticancer drugs. This study revealed that understanding the interaction between the tumor microenvironment and TCs is essential in designing experimental approaches to personalized medicine and to predict the effect of drugs.

• Journal of Information Technology Applications and Management
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• v.28 no.1
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• pp.83-93
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• 2021

The purpose of this study was to develop a personalized SMT (smart monitor target) game interface for game users who enjoy airsoft sports as individual purchases of SMT have increased since the advent of the untouched era. For this study, the UX (user experience) of the game interface was designed based on previous research. In particular, the personalized game service was reinforced by adding the CP (command post) of the SMT system that performs the home function of the console game, which was intended to help the user maintain immersed in the game in the personalized space of the SMT. Major design elements for the SMT game interface included layout, color, graphics, buttons, and text, and the interface design was proceeded based on them. After composing a grid with a layout in which the tab function was applied to the interface with a vertical three-segment structure and the outer margin value secured, the military camouflage pattern and texture were applied to the colored tone to perform graphics work. Targets and thumbnails were produced as illustrations using experts to ensure the consistency of the interface, and then function buttons and texts on each page were used concisely for intuitive information delivery. The design sources organized in this way were developed using the Unity engine. In the future, we hope that game user-centered personalized interfaces will continue to develop and provide differentiated services unique to SMT systems in the airsoft gun market.

• Smart Media Journal
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• v.9 no.1
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• pp.45-50
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• 2020

With the development of deep learning, studies using artificial neural networks based on deep learning in recommendation systems are being actively conducted. Especially, the recommendation system based on RNN (Recurrent Neural Network) shows good performance because it considers the sequential characteristics of data. This study proposes a travel route recommendation system using GRU(Gated Recurrent Unit) and Session-based Parallel Mini-batch which are RNN-based algorithm. This study improved the recommendation performance through an ensemble of top1 and bpr(Bayesian personalized ranking) error functions. In addition, it was confirmed that the RNN-based recommendation system considering the sequential characteristics in the data makes a recommendation reflecting the meaning of the travel destination inherent in the travel route.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.2
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• pp.100-105
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• 2009

In this paper, we Propose a browsing system to reduce the contents retrieval time in the personalized broadcasting system. For this purpose, we add a subgenre table between Classification DS and Summarization DS of MPEG-7 MDS. The subgenre includes a subgenre list to shorten the searching time of contents which we want to find. In addition we divide metadata into event and object using Summarization DS of the MPEG-7 MDS. In this way, the hierarchical browsing of broadcasting contents is made possible. This structure may reduce the complexity of search by storing event and object separately. Our simulation results show that the search time of the proposed system is shorter than that of the previous works.

• Journal of Digital Contents Society
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• v.11 no.4
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• pp.589-595
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• 2010

In this paper, we have designed and implemented a personalized health training system which provides health training methods using 3D animation based on the data from a professional trainer, after a trainee inputs individual physical characteristics. Many trainers at fitness centers provide only sketchy training method and usage of fitness machines not appropriate training method for trainee's physical characteristics. Individual characteristics. Individual characteristics prepared tabular input which consists of exercise goals, exercise areas, whether or not the normal movement, and RM. The system provides the training methods, the effects of exercise, and the health training motions through searching the database more accurately.

• Journal of the Korea Society of Computer and Information
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• v.13 no.7
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• pp.247-256
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• 2008

This research is to develop product retrieval system through simplified communication by applying intelligent agent technology based on automatically created domain ontology to present solution on problems with e-commerce system which searches in the web documents with a simple keyword. Ontology development extracts representative term based on classification information of international product classification code(UNSPSC) and jewelry websites that is applied to analogy relationship thesaurus to establish standardized ontology. The intelligent agent technology is applied to retrieval stage to support efficiency of information collection for users by designing and developing e-commerce system supported with semantic web. Moreover, it designs user profile to personalized search environment and provide personalized retrieval agent and retrieval environment with inference function to make available with fast information collection and accurate information search.