• Journal of the Korea Society of Computer and Information
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• v.27 no.1
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• pp.83-89
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• 2022

As a representative technique of recommender systems, collaborative filtering has been successfully in service through many commercial and academic systems. This technique recommends items highly rated by similar neighbor users, based on similarity of ratings on common items rated by two users. Recently research on time-aware recommender systems has been conducted, which attempts to improve system performance by reflecting user rating time of items. However, the decay rate uniform to past ratings has a risk of lowering the rating prediction performance of the system. This study proposes a rating time-aware similarity measure between users, which is a novel approach different from previous ones. The proposed approach considers changes of similarity value over time, not item rating time. In order to evaluate performance of the proposed method, experiments using various parameter values and types of time change functions are conducted, resulting in improving prediction accuracy of existing traditional similarity measures significantly.

• Journal of applied mathematics & informatics
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• v.28 no.1_2
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• pp.439-450
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• 2010

In this paper, we propose a new idea to evaluate the prediction accuracy of user's preference generated by memory-based collaborative filtering algorithm before prediction process in the recommender system. Our analysis results show the possibility of a pre-evaluation before the prediction process of users' preference of item's transaction on the web. Classification functions proposed in this study generate a user's rating pattern under certain conditions. In this research, we test whether classification functions select users who have lower prediction or higher prediction performance under collaborative filtering recommendation approach. The statistical test results will be based on the differences of the prediction accuracy of each user group which are classified by classification functions using the generative probability of specific rating. The characteristics of rating patterns of classified users will also be presented.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.2
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• pp.91-100
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• 1998

This paper is to study on rating system of some shrubs for pedestrian control with concentrate upon the density of branch. It was usd that Hibiscus syricacus L., Spiraea prunifolia var. simpliciflora Nak, Ligustrum obtusifolium S. et Z., Callicarpa dichotoma Raeusch., Rhoododendron mucrionulatum Turcz., Syringa vulgaris L., Weigela subsessilis L. H. Bailey, Cercis chinensis bunge, Forsythia koreana Nak., Euonymus alatus Sieb, Chaenomeles speciosa Nak., orbaria sorbifolia var. stellipila Max., Deutzia parviflora Bunge, Kerria japonica De Candolle, Prunus tomentosa Thunberg ex Murray, Purunus grandulosa for. albiplena Koehne. Shrubs are invesitgated ito the density of branch, the power of sprout, height, a rate of growth, hardness of naturalizaton, crown width and existence of thorns. Shrubs belonged to high group of rating system for pedestrian control were Euonymus alatus Sieb, Purunus grandulosa for. albiplena Koehne, Chaenomeles speciosa Nak., Spiraea prunifolia var. simpliciflora Nak., Prunus tomentosa Thunberg ex Murray, Rhododendron mucronulatum Turcz., Hibiscus syricacus L., Ligustrum obtusifolium S. et Z., Syringa vulgaris L., Weigela subsessilis L.H.Bailey.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.71-76
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• 2003

The purpose of this study is the development, application and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence, For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.

• Proceedings of the KIEE Conference
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• 2002.07c
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• pp.1455-1457
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• 2002

The real-time dynamic rating system(DRS) can provide the maximum ampacity within required periods, so it can help the transmission-line operation more safely and efficiently. Because the conductor temperature is the main limit of increasing rating current, conductor temperature monitoring(CTM) technology is the basic to DRS. In this paper, real-time CTM was developed for 345kV XLPE cable in tunnel and we have also compared the CTM result of this study with the result according to IEC 287 and JCS 168 thermal parameters.

• Progress in Superconductivity and Cryogenics
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• v.7 no.2
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• pp.16-20
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• 2005

As power systems grow more complex and power demands increase, the fault current tends to gradually increase. In the near future, the fault current will exceed a circuit breaker rating for some substations, which is an especially important issue in the Seoul metropolitan area because of its highly meshed configuration. Currently, the Korean power system is regulated by changing the 154kV system configuration from a loop connection to a radial system, by splitting the bus where load balance can be achieved, and by upgrading the circuit breaker rating. A development project applying 154kV Superconducting Fault Current Limiter (SFCL) to 154kV transmission systems is proceeding with implementation slated for after 2010. In this paper, SFCL is applied to reduce the fault current in power systems according to two different application schemes and their technical impacts are evaluated. The results indicate that both application schemes can regulate the fault current under the rating of circuit breaker, however, applying SFCL to the bus-tie location is much more appropriate from an economic view point.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2003.05a
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• pp.474-483
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• 2003

A number of studies for corporate bond rating classification problems have demonstrated that artificial intelligence approaches such as Case-based reasoning (CBR) can be alternative methodologies to statistical techniques. CBR is a problem solving technique in that the case specific knowledge of past experience is utilized to find a most similar solution to the new problems. To build a successful CBR system to deal with human information processing, the representation of knowledge of each attribute is an important key factor We propose a hybrid approach of using fuzzy sets that describe the approximate phenomena of the real world because it handles inexact knowledge represented by common linguistic terms in a similar way as human reasoning compared to the other existing techniques. Integration of fuzzy sets with CBR is important to develop effective methods for dealing with vague and incomplete knowledge to statistical represent using membership value of fuzzy sets in CBR.

• Health Policy and Management
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• v.15 no.1
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• pp.97-117
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• 2005

This study was designed to compare the differences m results of supervisor and subordinate rating. Data was collected from personnel evaluation and subordinate rating results for middle managers(n=68) in hospital from 3rd January to 20th March in 2004. Supervisor rating consisted of performance, ability and attitude evaluation. Subordinate rating consisted of leadership, ability and attitude evaluation. Collected data included sociodemographic characteristics, work department, work level, years of work, years at present level and whether working in a patient serving department. The difference of standardized supervisor and subordinate rating score was used to define groups as 'higher in supervisor rating group'. Groups were defined in total score, ability score and attitude score. Main results were as follows: 1. In total score, sectional chiefs were apt to be 'higher in subordinate rating group' while chief clerks were apt to be 'similar group' or 'higher in supervisor rating group'. Staffs in patient serving department were likely to be 'higher in supervisor rating group' and staffs in non-patient serving department were likely to be 'higher in subordinate rating group'. All these results were statistically significant. 2. In ability score, there were no statistically significant differences in age, sex, years of education, work department, work level, years of work and whether working in a patient serving department among 'higher in supervisor rating group', 'similar group' and 'higher in subordinate rating group'. 3. In attitude score, staffs in the department of medical affairs and the department of administration were apt to be 'higher in subordinate rating group'. Staffs in the department of nursing were apt to be 'higher in supervisor rating group'. Staffs in a patient serving department were likely to be 'higher in supervisor rating group' and staffs in a non-patient serving department were likely to be 'higher in subordinate rating group'. All these results were statistically significant. 4. Logistic analysis about total score showed that sectional chiefs had higher Odds Ratio(OR) to be in 'higher in subordinate rating group'. Staffs in a non-patient serving department had higher OR to be in 'higher in subordinate rating group'. Both these results were statistically significant. 5. Logistic analysis about ability score showed that sectional chiefs had higher OR to be in 'higher in subordinate rating group'. Staffs in a non-patient serving department had higher OR to be in 'higher in subordinate rating group'. These results were not statistically significant. 6. Logistic analysis about total score showed that sectional chiefs had higher OR to be in 'higher in subordinate rating group', but the difference was not statistically significant. Staffs in a non-patient serving department had significantly higher OR to be in 'higher in subordinate rating group'. In conclusion, there is no clear superiority between supervisor and subordinate rating in personnel evaluation. It would be better to use a mixed model. It's also suggested to use an intervening rate of application or scores considering work levels and work department in personnel evaluation. These results would be helpful for hospitals planning a supervisor and subordinate rating system for personnel evaluation.

• The Journal of Internal Korean Medicine
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• v.33 no.1
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• pp.102-110
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• 2012

Multiple system atrophy (MSA) is a sporadic progressive neurodegenerative disorder characterized clinically by various combinations of parkinsonian, autonomic, cerebellar, or pyramidal signs and pathologically by cell loss, gliosis, and ${\alpha}$-synuclein-positive glial cytoplasmic inclusions in several brain and spinal cord structures. This is a clinical report about a 69-year-old female who had MSA treated by oriental medical treatment and evaluated by Unified Multiple System Atrophy Rating Scale (UMSARS). The patient was treated with herb medicine Chungsimyeonj-aeumgami(淸心蓮子飮加味), acupuncture, moxibustion and cupping. After treatment, the patient's symptoms improved meaningfully and the score decreased in UMSARS Part I, II. This suggests that oriental medical treatment could be effective to improve MSA patients' symptoms. It is necessary to have more observations and many cases of patients with MSA.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.125-134
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• 2021

With the rapid development of the film industry, the number of films is significantly increasing and movie recommendation system can help user to predict the preferences of users based on their past behavior or feedback. This paper proposes a movie recommendation system based on the latent factor model with the adjustment of mean and bias in rating. Singular value decomposition is used to decompose the rating matrix and stochastic gradient descent is used to optimize the parameters for least-square loss function. And root mean square error is used to evaluate the performance of the proposed system. We implement the proposed system with Surprise package. The simulation results shows that root mean square error is 0.671 and the proposed system has good performance compared to other papers.