• Korea Real Estate Review
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• v.24 no.1
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• pp.91-104
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• 2014

This paper studied condo selection attributes that affected satisfaction, recommendation and revisitation, in particular, investigated gender and age differences. Research target is the group who revisited time-sharing condominium within one year. The paper seeks to understand factors that affect and contribute to customer satisfaction and intentions for reuse. This study model was analyzed by the basic statistical analysis, factor analysis, reliability analysis and multiple analysis, using SPSS 18.0 and AMOS 18.0. We found that 5 condo selection attributes that have significant affect on user satisfaction: facility, service, product, accessibility and expense. Furthermore it was evident that user satisfaction has a significant effect on condo recommendation and intentions of reuse. With regard to sex, for male users expense, accessibility and service had a significant effect on their satisfaction level, while for female users, product was most important. User satisfaction both have a significant effect on recommendation and intentions of reuse but for females this was more evident. Regarding the age, for 20~30 age band, service and product factor had a significant effect on user satisfaction in order, whereas, for the age band of over 40s, expense, product and facility factors were important. User satisfaction of both have a significant effect on recommendation and intentions of reuse. In the meantime user satisfaction of 20~30 age band had a bigger positive significant effect on recommendation and intentions of reuse than the age band over 40s.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.147-161
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• 2010

As broadcasting and communication are converged recently, communication is jointed to TV. TV viewing has brought about many changes. The IPTV (Internet Protocol Television) provides information service, movie contents, broadcast, etc. through internet with live programs + VOD (Video on demand) jointed. Using communication network, it becomes an issue of new business. In addition, new technical issues have been created by imaging technology for the service, networking technology without video cuts, security technologies to protect copyright, etc. Through this IPTV network, users can watch their desired programs when they want. However, IPTV has difficulties in search approach, menu approach, or finding programs. Menu approach spends a lot of time in approaching programs desired. Search approach can't be found when title, genre, name of actors, etc. are not known. In addition, inserting letters through remote control have problems. However, the bigger problem is that many times users are not usually ware of the services they use. Thus, to resolve difficulties when selecting VOD service in IPTV, a personalized service is recommended, which enhance users' satisfaction and use your time, efficiently. This paper provides appropriate programs which are fit to individuals not to save time in order to solve IPTV's shortcomings through filtering and recommendation-related system. The proposed recommendation system collects TV program information, the user's preferred program genres and detailed genre, channel, watching program, and information on viewing time based on individual records of watching IPTV. To look for these kinds of similarities, similarities can be compared by using ontology for TV programs. The reason to use these is because the distance of program can be measured by the similarity comparison. TV program ontology we are using is one extracted from TV-Anytime metadata which represents semantic nature. Also, ontology expresses the contents and features in figures. Through world net, vocabulary similarity is determined. All the words described on the programs are expanded into upper and lower classes for word similarity decision. The average of described key words was measured. The criterion of distance calculated ties similar programs through K-medoids dividing method. K-medoids dividing method is a dividing way to divide classified groups into ones with similar characteristics. This K-medoids method sets K-unit representative objects. Here, distance from representative object sets temporary distance and colonize it. Through algorithm, when the initial n-unit objects are tried to be divided into K-units. The optimal object must be found through repeated trials after selecting representative object temporarily. Through this course, similar programs must be colonized. Selecting programs through group analysis, weight should be given to the recommendation. The way to provide weight with recommendation is as the follows. When each group recommends programs, similar programs near representative objects will be recommended to users. The formula to calculate the distance is same as measure similar distance. It will be a basic figure which determines the rankings of recommended programs. Weight is used to calculate the number of watching lists. As the more programs are, the higher weight will be loaded. This is defined as cluster weight. Through this, sub-TV programs which are representative of the groups must be selected. The final TV programs ranks must be determined. However, the group-representative TV programs include errors. Therefore, weights must be added to TV program viewing preference. They must determine the finalranks.Based on this, our customers prefer proposed to recommend contents. So, based on the proposed method this paper suggested, experiment was carried out in controlled environment. Through experiment, the superiority of the proposed method is shown, compared to existing ways.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.14 no.5
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• pp.159-173
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• 2019

The purpose of this study is to examine the effect of service quality of banks on customer satisfaction and recommendation intention through empirical analysis. In particular, the focus was on the differences of the causal effect between PB(Private Banking) customers and regular customers. For this study, two groups were surveyed and 428 valid questionnaires were analyzed. The hypothesis was tested with a structural equation model using AMOS 23.0. As a result, empathy, reliability and tangibles of bank service quality had a positive(+) effect on customer satisfaction. However, responsiveness and assurance were not statistically significant. On the other hand, customer satisfaction has a positive effect on recommendation intention. This study was conducted to compare the two groups, PB customers and regular customers, and found a significant difference. In the PB customers group, tangibles had a positive effect on customer satisfaction, but no other factors were supported. On the other hand, in the regular customers group, empathy and reliability had a positive effect on customer satisfaction while responsiveness, assurance, and tangibles were not supported. Customer satisfaction were analyzed to have a positive influence on recommendation intention in both groups. These findings are academically significant by applying the SERVQUAL factors to banking services and revealing the differences between the PB customers and regular customers. In practice, it is meaningful in that it provided banks with the insights needed for future segmentation and management of customer groups.

• Journal of Technologic Dentistry
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• v.38 no.3
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• pp.185-191
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• 2016

Purpose: The purpose of this study were to evaluate the quality of dental prostheses printed by 3-dimensional printing system. Methods: Mater model was prepared and ten study models were fabricated. Ten single crowns were printed by 3D-printing system(Resin group) and another ten single crowns using casting method were manufactured(Metal group). The marginal adaptation of single crowns were measured using by silicone replica technique. Silicone replicas were sectioned four times. The marginal adaptations were evaluated using by digital microscope. Statistical analyses were performed with Mann-Whitney test(${\alpha}=0.05$). Results: $Mean{\pm}standard$ deviations of all marginal adaptations were $92.1(20.0){\mu}m$ for Metal group and $69.7(12.3){\mu}m$ for Resin group. Two groups were no statistically significant differences(p>0.05). Conclusion: Marginal adaptation of single crowns printed by 3D-printing system were ranged within the clinical recommendation.

• Journal of Korean society of Dental Hygiene
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• v.10 no.2
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• pp.393-411
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• 2010

Objectives : The purpose of this study was to examine factors related to the satisfaction level of patients with dental services. Methods : The subjects in this study were 200 patients at three different dental clinics in South Gyeongsang Province, on whom a survey was conducted from June 1 to July 31, 2009. The collected data were analyzed, and the findings of the study were as follows. Results : In regard to the general characteristics of the patients investigated, the women(61.5%) out-numbered the men. By age, those who were at the age of 30 and down made up the largest age group(47.0%). By academic background, the greatest group received junior-college education(54.0%). By occupation, the company employees constituted the largest group (50.5%). By income, the greatest group earned an income of 2 to 2.99 million won(75.0%). Second, as to connections between the characteristics of dental treatment and the reason of choosing the dental clinics, the largest group(70.4%) chose the dental clinics by word of mouth or the recommendation of others. Concerning the reason of dissatisfaction, the biggest group(72.7%) was unsatisfied with medical costs. As for the degree of explicit complaint, the greatest group(49.7%) sort of complained about what made them dissatisfied. Regarding the type of treatment, the biggest group(49.0%) received prosthodontic treatment. In relation to fear for dental treatment, the largest group(34.0%) feared receiving the treatment, and the biggest group(42.6%) did that due to the sound of machines. Third, satisfaction with services(0.762) had the closest correlation to overall satisfaction level, followed by satisfaction with employees(0.735), satisfaction with dentists(0.644) and satisfaction with convenient facilities (0.579). Fourth, the factors that affected overall satisfaction level were gender, the reason of choosing the dental clinic, satisfaction with dentists, satisfaction with employees, satisfaction with services and satisfaction with convenient facilities. The patients who were better satisfied with services(p<0.001), who were more contented with dentists(p<0.001), who chose the dental clinics by the recommendation of others(p<0.01), who were male(p<0.05), who were more gratified with employees(p<0.05) and who were more contented with convenient facilities expressed better overall satisfaction. Conclusions : The above-mentioned findings suggested that dental institutions should keep track of the expectations of patients to prepare differentiated strategies for marketing and human-resources development in consideration of their own circumstances to boost the satisfaction level of patients. Specifically, it's required to heighten the satisfaction level of patients with dentists.

• Journal of the Korean Applied Science and Technology
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• v.37 no.3
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• pp.473-483
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• 2020

This paper proposes a tourism recommendation system in intelligent cloud environment using information of tourist behavior applied with perceived value. This proposed system applied tourist information and empirical analysis information that reflected the perceptual value of tourists in their behavior to the tourism recommendation system using wide and deep learning technology. This proposal system was applied to the tourism recommendation system by collecting and analyzing various tourist information that can be collected and analyzing the values that tourists were usually aware of and the intentions of people's behavior. It provides empirical information by analyzing and mapping the association of tourism information, perceived value and behavior to tourism platforms in various fields that have been used. In addition, the tourism recommendation system using wide and deep learning technology, which can achieve both memorization and generalization in one model by learning linear model components and neural only components together, and the method of pipeline operation was presented. As a result of applying wide and deep learning model, the recommendation system presented in this paper showed that the app subscription rate on the visiting page of the tourism-related app store increased by 3.9% compared to the control group, and the other 1% group applied a model using only the same variables and only the deep side of the neural network structure, resulting in a 1% increase in subscription rate compared to the model using only the deep side. In addition, by measuring the area (AUC) below the receiver operating characteristic curve for the dataset, offline AUC was also derived that the wide-and-deep learning model was somewhat higher, but more influential in online traffic.

• Journal of Nutrition and Health
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• v.25 no.2
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• pp.150-161
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• 1992

The purpose of this study was to evaluate the riboflavin status of primary school children. Fiftyone subjects were selected as obese group and fiftyfive subjects were selected as control group according to Body Mass Index(BMI) of fifth-graders at a primary school in Taegu. For each subject information on nutrient intake and daily activity pattern were obtained by questionnaire. The riboflavin status was evaluated by urinary riboflavin exvretion The daily energy expenditure per kilogram of body weight was significantly lower in obese group(=47kcal/day) than in control group(=58kcal/day) (p<0.001) However the entire energy consumption was siginificantly greater in the obese children(=2005kcal/day) than their nono-baser peers(=1837kcal/day)(p<0.001). Riboflavin intake was 0.67mg/100kcal in the control group and 0.61mg/1000kcal in the obese group. Thus intakes for both groups met the current group and control group were 86.9$\mu\textrm{g}$/day and 98.7$\mu\textrm{g}$/day. repectively. There was no significnat Assesment of clinical signs of riboflavin deficiency indicated that angular lesion was 4.7% and glossitis was 6.6% of all subjects. Thirty one percent of subjects excrete riboflavin below 78$\mu\textrm{g}$/g creatinine which is defined as deficient. Therefore this group would be considered at high risk for developing riboflavin deficiency. From this study current recommendation of 0.6mg/1000kcal of riboflavin intake may not be adequate during growth and associated stress.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.504-510
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• 2009

Recently, personalized-adaptive services became the center of interest in the world. However the services about music are not widely diffused out. That is because the analyzing of music information is more difficult than analyzing of text information. In this paper, we propose a music recommendation system which provides personalized services. The system keeps a user's listening list and analyzes it to select pieces of music similar to the user's preference. For analysis, the system extracts properties from the sound wave of music and the time when the user listens to music. Based on the properties, a piece of music is mapped into a point in the property space and the time is converted into the weight of the point. At this time, if we select and analyze the group which is selected by user frequently, we can understand user's taste. However, it is not easy to predict how many groups are formed. To solve this problem, we apply the K-means clustering algorithm to the weighted points. We modified the K-means algorithm so that the number of clusters is dynamically changed. This manner limits a diameter so that we can apply this algorithm effectively when we know the range of data. By this algorithm we can find the center of each group and recommend the similar music with the group. We also consider the time when music is released. When recommending, the system selects pieces of music which is close to and released contemporarily with the user's preference. We perform experiments with one hundred pieces of music. The result shows that our proposed algorithm is effective.

• Journal of radiological science and technology
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• v.40 no.3
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• pp.355-361
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• 2017

Pediatrics are more sensibility to radiation than adults and because they are organs that are not completely grown, they have a life expectancy that can be adversely affected by exposure. Therefore, the management of exposure dose is more important than the case of adult. The purpose of this study was to determine the suitability of the 10 year old phantom for the 5 year old pediatric's recommendation and the incident surface dose, and to measure the organ absorbed dose. This study is compared the organ absorbed dose and the entrance surface dose in the clinical conditions at 5 and 10 years old pediatric. Clinical 5 year old condition was slightly higher than recommendation condition and 10 year old condition was very high. In addition, recommendation condition ESD was found to be 43% higher than the ESD of the 5 year old group and the ESD of the 10 year old group was 126% higher than that of the 5 year old group. The recommended ESD at 5 years old and the ESD according to clinical imaging conditions were 31.6%. There was no significant difference between the 5 year old recommended exposure conditions and the organ absorbed dose due to clinical exposure conditions, but there was a large difference between the Chest and Pelvic. However, it was found that there was a remarkable difference when comparing the organ absorbed dose by 10 year clinical exposure conditions. Therefore, more detailed standard exposure dose for the recommended dose of pediatric should be studied.