• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.201-207
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• 2022

In this paper, we propose a movie recommendation model that uses the users' ratings as well as their reviews. To understand the user's preference from multicriteria perspectives, the proposed model is designed to apply attribute-based sentiment analysis to the reviews. For doing this, it divides the reviews left by customers into multicriteria components according to its implicit attributes, and applies BERT-based sentiment analysis to each of them. After that, our model selectively combines the attributes that each user considers important to CF to generate recommendation results. To validate usefulness of the proposed model, we applied it to the real-world movie recommendation case. Experimental results showed that the accuracy of the proposed model was improved compared to the traditional CF. This study has academic and practical significance since it presents a new approach to select and use models in consideration of individual characteristics, and to derive various attributes from a review instead of evaluating each of them.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.2
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• pp.1-11
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• 2010

The provision of warning information on upcoming hazards leading to potential crash occurrence is a significant countermeasure to prevent crashes on the highway. This study presents a methodology for selecting more effective warning messages using a multi-criteria value function. The understandability, preference level, and message reading time were used as measures of effectiveness (MOE) for messages. Expert judgements were incorporated into the value function by analytical hierarchical process (AHP) technique. Field experiments to evaluate the warning messages were conducted in a testbed section on the Jungboo-Naeryuk freeway. The proposed methodology would be a useful tool to support the design of various traffic information messages.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.476-479
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• 2004

In the process of industrialization of our country in 1970's, Korea's housing strategy has focused on housing supply. Rapid completion and supply of apartment house buildings have caused a problem of their early deterioration due to their poor quality. In 1987 Housing Construction Promotion Act, therefore, included new regulations on housing re-construction. In July 2001, other new regulations on remodeling apartment buildings were also included in the Act. Reconstruction and remodeling have been considered to deal with such problems. This study suggests an appraisal criteria if they can select reconstruction or remodeling method in conducting their apartment building project. At first, evaluation items should be selected by the criteria of function31ity and economical efficiency. Second, the selected item is screened by AHP and multi-criteria decision-making methods. The result of study shows that the owners of apartment units will be able to select reasonable alternatives through the suggested appraisal method

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.103-104
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• 2012

본 연구에서는 도시 소유역간 상대적 침수위험도 산정을 위하여 엔트로피(Entropy) 기법 및 다기준의사결정 방법의 하나인 프로메티(Preference Ranking Organization METHod for Enrichment Evaluations, PROMETHEE)를 적용하였다. 이에 따라 도시유역 침수위험도 산정과 관련된 항목 6개를 선정하여 평가기준으로 적용하였으며, 실제 도시유역에 적용 및 해당 유역의 과거 집중호우에 따른 침수이력과 비교하였다.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.25-32
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• 2013

Due to increasing competition of globalization and fast technological improvements the appropriate method for evaluating and selecting IS-personnel is one of the key factors for an organization's success. Personnel selection is a multi-criteria decision-making (MCDM) problem which consists of both qualitative and quantitative metrics. Although many articles have discussed various knowledge and skills IS personnel should possess, no specific model for IS personnel selection and evaluation, to our knowledge, has been published up to now. After reviewing the IS personnel's important characteristics, we propose an approach for categorizing the IS personnel based on their skills, ability, and knowledge during evaluation and selection process. Our proposed approach is derived from a model of neural network algorithm. We have adapted and implemented the fuzzy ART algorithm with Jaccard choice function. The result of an illustrative numerical example is proposed to demonstrate the easiness and effectiveness of our approach.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.3
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• pp.639-645
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• 2015

Recently, a study on the commercialization of Rope type Platform Safe Door (RPSD) technology has commenced. The study focuses on RPSD, in which a rope screen ascends to allow safe passage from the platform to the transit vehicle in aboveground stations. Currently, a pilot installation has taken in place with Daegu Metro Line 2 in MoonYang station starting from March of 2013. However, there is a need to select an appropriate pilot installation's object for the improvement in the future RPSD. An appropriate designation would correspond with the needs of the railroad corporation and as a historic railway platform with safe facilities. This study tried to usa Analytic Hierarchy Process (AHP) to determine the priority of the KTX stations to attain a list of appropriate designations for future RPSD installations by analyzing the followings: management of the facilities, operational risks, and intent of business projects. As a case study, it was applied to the evaluation of the KTX stations. For the application, it used relative measurement to calculate the weight of upper level structuring, and absolute measurement for low level structuring instead of pairwise comparisons.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.195-204
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• 2008

Multi-Criteria Analysis is one method for optimizing decisions that include numerous characteristics and objective functions. The Analytic Hierarchy Process (AHP) is used as a general Multi-Criteria Analysis considering many critical issues. However, since validation procedures for the decision reliability of AHP valuers had been left off existing methodologies, a new methodology including such validation procedures is required to make more reliable decisions. In this research, idea decision results are derived using Monte Carlo Simulation in cases where AHP valuers do not have expertise in the specific project, and these results are compared with the results derived from experts to develop a new analysis model to make more reliable decisions. Finally, this new analysis is applied to various field case studies of road and rail carried out by the Korea Development Institute (KDI) between 2003 and 2006 to validate the new analysis model. The study found that approximately 20% of decisions resulting from the existing methodology are considered prudent. In future studies, the authors suggest analyzing the correlation between initial weights and final results since final results are enormously influenced by the initial weight.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2004.05a
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• pp.341-346
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• 2004

In the present work, for various energy and electricity generating systems to be compared in view of integrated social impacts, nuclear, coal-fired, heavy oil-fired, and LNG, and hydroelectricity systems are considered as electricity generating options. The following assessment factors are selected: economic effect, health effect, environmental effect, and benefit at the national level. As a preliminary study, these factors are represented as power generation cost, estimated mortality, Carbon Dioxide gas emission, and fuel supply stability, respectively. For integrated representation of a multi-criteria decision-making (MCDM) problem, radar charts are introduced to facilitate a comparative recognition of estimates. In the near future, based on the estimates, a MCDM methodology for both qualitative and quantitative comparison will be developed.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.510-516
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• 2003

연안관리 정책을 결정하기 위해서는 다양한 정보의 수집과 이를 체계적으로 관리하고 분석할 수 있는 기법이 필요하다. 특히, 다양한 이해집단과 목적들이 상충하는 지역의 특성을 파악하기 위해서는 환경, 사회, 경제적인 기준 및 의사결정자의 가치체계가 반영될 수 있어야 하며, 선호도가 반영된 요소를 효율적으로 분석할 수 있어야 한다. 이에, 본 연구에서는 공간자료의 처리 및 분석이 용이한 GIS 환경에 다기준 분석법, 그 중에서도 AHP 모형을 결합하는 방법을 다루어 보았다. 분석과정을 살펴보면, 본 연구에서는 지역에 영향을 미치는 사회ㆍ경제적인 지표, 환경 지표를 정하였고, 이런 지표들의 데이터를 GIS라는 도구를 통하여 분석이 용이하도록 변환시켰다. 한편, 이 지역에 영향을 미치는 각 기준들의 중요성을 파악하여 의사결정자의 의견을 반영할 수 있도록 다기준 분석법의 하나인 AHP를 이용하여 가중치를 산정하였다. 다음으로, 다양한 출처의 자료를 표준화하여 GIS의 래스터 자료로 구축한 후, 가중치를 적용한 개별 레이어를 지도대수와 중첩분석을 이용하여 최종 결과 레이어를 생성하였다. 생성된 최종 결과 레이어 상의 공간의 대안인 각 셀 값을 비교ㆍ분석하였다. 이로 인한 결과는 연안의 유한한 자원과 공간의 다양한 이용상태를 관리하기 위한 해안과 육상의 정보를 제공할 수 있다. GIS와 다기준 분석을 통합함으로써 다양한 출처의 공간정보를 분석하고 연안의 현 상태를 밝힐 수 있다. 또한, 이것은 분석 결과가 단순하고 명확하게 설명되어 정책 결정자에게 유용한 정보를 제공할 뿐만 아니라, 이 정보를 이용하여 실질적인 연안관리계획을 수립하는데 도움이 된다.가능성 0.5이상의 면적은 59%를 차지하였다.퇴적이 우세한 것으로 관측되었다.보체계의 구축사업의 시각이 행정정보화, 생활정보화, 산업정보화 등 다양한 분야와 결합하여 보다 큰 시너지 효과와 사용자 중심의 서비스 개선을 창출할 수 있는 기반을 제공할 것을 기대해 본다.. 이상의 결과를 종합해볼 때, ${\beta}$-glucan은 고용량일 때 직접적으로 또는 $IFN-{\gamma}$ 존재시에는 저용량에서도 복강 큰 포식세로를 활성화시킬 뿐 아니라, 탐식효율도 높임으로써 면역기능을 증진 시키는 것으로 나타났고, 그 효과는 crude ${\beta}$-glucan의 추출조건에 따라 달라지는 것을 알 수 있었다.eveloped. Design concepts and control methods of a new crane will be introduced in this paper.and momentum balance was applied to the fluid field of bundle. while the movement of′ individual material was taken into account. The constitutive model relating the surface force and the deformation of bundle was introduced by considering a representative prodedure that stands for the bundle movement. Then a fundamental equations system could be sim