• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.139-140
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• 2018

본 논문에서는 지도 기계 학습 알고리즘 중 하나인 Naive Bayesian (NB) 알고리즘의 데이터 분류 정확도를 향상시키기 위하여 데이터 속성에 Weight를 부여하는 새로운 기법을 제안하였다. 기존에 Decision Tree(DT) 알고리즘의 깊이를 이용하여 Weigth를 부여하는 방법이 제안되었으나, DT를 구축하는데 오버헤드가 크기 때문에 데이터의 실시간 분석이나 자원 제한적인 환경에서의 적용은 어렵다는 단점이 있다. 이를 해결하기 위하여 본 논문에서는 최소한의 데이터를 사용하여 신속하게 DT를 구축하는 Very Fast Decision Tree (VFDT) 알고리즘 기반의 Weight 부여 기법을 제안함으로써 적은 오버헤드로 NB의 정확도를 향상시킨다.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.439-445
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• 2000

다차원의 속성들을 포함한 대용량의 데이터베이스 또는 점보 저장소의 데이터로부터 지식을 추출하고 이를 활용하기 위해서는 데이터 마이닝의 인공지능 기법 중 기계학습을 활용할 수 있다. 본 논문은 질의어를 바탕으로 각 작성들에 가중치를 적용하여 사용자가 원하는 데이터 집합을 분류하고, 사용자 피드백을 통하여 속성 가중치를 동적으로 변화시킴으로써 검색결과를 향상시키는 방법을 제안한다. 본 논문에서는 데이터 집합을 분류해내기 위해서 각 속성간의 거리에 가중치를 적용하는 k-nearest neighbor 분류법을 사용하였고, 속성 가중치를 동적으로 변화시키는 규칙을 추출하기 위한 방법으로는 결정 트리 생성에 의한 규칙(decision rule) 생성 방법을 적용하였다. 검색결과 향상을 \ulcorner이기 위한 실험으로써 온라인 커플매칭(online couple-matching) 시스템의 핵심부문을 구현하고 이를 적용하였다.

• Journal of Korean Society for Quality Management
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• v.25 no.2
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• pp.169-188
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• 1997

The purpose of this study is concerned with suggesting a new a, pp.oach to evaluating the overall product quality in the sense of the relative efficiency of products, whose quality is measured with 8-dimensional attributes, suggested by Garvin. The attributes included 8 quality measures, that is, performance, features, reliability, conformance, durability, serviceabilit, aesthetics, and perceived quality. This study, also, introduced DEA(Data Envelopment Analysis) as an evaluation tool to tackle the problem of how to measure one product against another when each product can be measured along a number of dimensions, and given that there exists no a priori satisfactory weighting scheme to combine these dimensions into an overall rating for each products. In order to a, pp.y the DEA to evaluating the products, we must define two concepts, such as DMU(Decision Making Units) and input-output relationship. Finally, the suggested method in this study was validated through a case study of the electric jar, and this DEA a, pp.oach can be used in evaluating the other products with multi-attrribute quality.

• Journal of the Ergonomics Society of Korea
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• v.31 no.1
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• pp.63-76
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• 2012

Objective: The main objective of this study is to propose a user-centered assessment metric for ubiquitous services. Background: As the ubiquitous era took off, the interactions between ubiquitous services and users have come to take an important position. It is essential to conceptualize a new assessment model that considers human-system interaction capability with a user-centered design perspective. Method: The evaluation model for the interactivity of ubiquitous service was approached from the concept of usability and inter-personality of services. As a validation study, suggested assessment metric was utilized to evaluate the u-Home service. Priority weighting of each assessment metric was derived using the quantification type-I analysis. Results: To evaluate interactivity, this study suggested a quantitative metric for user testing performed after classifying the interactivity characteristics to contextualization; ubiquity; user experience; and service capability. Conclusion: This study suggest the metric for the ubiquitous service that are experienced in real life, and introduced the concept of ubiquitous service interactivity. Application: The suggested evaluation metric can be used to evaluate interactivity level of ubiquitous service and identify the potential problem and usability requirements at the early stage of service development.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.3
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• pp.129-144
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• 2013

Recognizing a limits on quantitative evaluation of cultural contents' and for its betterment, study aims developing a qualitative evaluation model. For this study, Reception Theory, Semiotics and Psychology were derived for epistemological dimension to contemplate culture contents' essential attribute. To be concrete, cultural contents was examined as experiential products, emotional products, rememberable products and texts. Also, codes of fun, emotion and culture were discussed as intrinsic attributes for cultural contents and how those attributes were expressed or composed in cultural contents was discussed as well. Evaluation items were extracted based on final discussion at the epistemic level, set up the final evaluation model by taking experts' advices on each items. With all those outcomes, qualitative evaluation model for cultural contents was developed. For the importance of each index in the model, priority was granted by weighting on each index. Lastly, evaluation scale was developed for each index. The culture contents' evaluation model developed in study is meaningful not only in drawing qualitative evaluation items of video(image) contents and developing the index and model for the first time, but also its possibility of wide use for other genres.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2996-3011
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• 2017

With rapid growth of web technology and dissemination of smart devices, social networking service(SNS) is widely used. As a result, huge amount of data are generated from SNS such as Twitter, and sentiment analysis of SNS data is very important for various applications and services. In the existing sentiment analysis based on the $Na{\ddot{i}}ve$ Bayes algorithm, a same number of attributes is usually employed to estimate the weight of each class. Moreover, uncountable and meaningless attributes are included. This results in decreased accuracy of sentiment analysis. In this paper two methods are proposed to resolve these issues, which reflect the difference of the number of positive words and negative words in calculating the weights, and eliminate insignificant words in the feature selection step using Multinomial $Na{\ddot{i}}ve$ Bayes(MNB) algorithm. Performance comparison demonstrates that the proposed scheme significantly increases the accuracy compared to the existing Multivariate Bernoulli $Na{\ddot{i}}ve$ Bayes(BNB) algorithm and MNB scheme.

• The Journal of Information Systems
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• v.25 no.2
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• pp.153-171
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• 2016

Purpose This study suggests the development of forecasting model for local cable TV advertisement. In order to verify the expected effect of the suggestion, using the causal loop map of System Dynamics, the factors affecting the prospects of cable TV commercial market were divided into 5 groups. Then targeting 97 people involved in the cable TV commercial market in Busan, Ulsan, and Gyeongnam, a survey was conducted on their perception of the current status of local advertisement market and future prospect. Design/methodology/approach The analysis of the collected data shows that workers in advertising and advertisers perceive the influence of cable TV as an advertising media to be high, while clearly understanding the problems of cable TV commercial market. Based on this the effects on the prospects of cable TV commercial market were analyzed and a forecasting method called Weighted Moving Average was applied. In order to improve accuracy of the added value of Weighted Moving Average, the 5 factors were divided into qualitative factors and quantitative factors, and using Multi-attribute Decision Making method, all the factors were normalized and weighting factors were deduced. The result of simulating the prospects of cable TV commercial market using Weighted Moving Average, both qualitative and quantitative factors showed downward turn in the market prospect for the following 10 years. Findings The result reflects generally negative perception of advertisement viewers about the prospects of cable TV commercial market. Compared to the previous studies on domestic cable TV commercials that focused on policy suggestions and surveys on perception of current status, this study has its significance in that it used scientific method and simulation for verification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1581-1586
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• 2016

In this paper, we propose a central disaster monitoring system of the forest fire. This system provides the safe-zone and detection to reduce the suppression efforts. In existing system, it has a few providing the predicting of wildfire spread model and speed through topography, weather, fuel factor. This paper focus on the forest fire diffusion model and predictions of the path identified to ensure the safe zone. Also we have considering the forest fire of moving direction and speed for fire suppression and monitering. The proposed algorithm could provide the technique to analyze the attribute information that temperature, wind, smoke measured over time. This proposed central observing monitoring system could provide the moving direction of spred out forecast wildfire. This observing and monitering system analyze and simulation for the moving speed and direction forest fire, it could be able to predict and training the forest fire fighters in a given environment.

• Journal of Korea Society of Industrial Information Systems
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• v.20 no.4
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• pp.1-9
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• 2015

This paper proposes CAC method that is more efficient for RRM using game theory combined with Multiple Attribute Decision Making(MADM). Because users request services with different Quality of Service(QoS), the network preference values to alternative networks for each service are calculated by MADM methods such as Grey Relational Analysis(GRA), Simple Additive Weighting(SAW) and Technique for Order Preference by Similarity to Ideal Solution(TOPSIS). According to a utility function representing preference value, non-cooperative game is played, and then network provider select the requested service that provide maximum payoff. The appropriate service is selected through Nash Equilibrium that is the solution of game and the game is played repeated. We analyze two overlaid networks among four Wireless LAN(WLAN) systems with different properties. Simulation results show that proposed MADM techniques have same outcomes for every game round.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.307-318
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• 2021

The objective of this study is to analyze the performance of Islamic banks with the Maqashid Shariah approach. The analysis technique used is the Simple Additive Weighting Method (SAW) to solve multi-attribute decision problems. The sampling technique used was purposive sampling while the data came from the annual report of each bank. The results showed that the BTPN Shariah (BTPNS) and Bank Muamalat Indonesia (BMI) are ranked first and second respectively on the Maqashid Shariah Index (MSI) with values of 0.265429 and 0.237110 respectively. Panin Dubai Shariah Bank (PDSB) ranked third with an MSI value of 0.180733, followed by BCA Shariah which ranked fourth with an MSI value of 0.151299. BRI Shariah ranked fifth with an MSI value of 0.128606, followed by BNI Shariah which ranked sixth with an MSI value of 0.124661. Bank Mega Shariah ranked last with an MSI value of 0.087068. Furthermore, there is a relationship (correlation) between ROE, ROA, and OEOI and MSI since each data has a value of 0.000, 0.000, 0.050, and 0.001 respectively, which is smaller than the significance value of 0.05. On the other hand, NPF, TPF, and Asset Growth Rates do not correlate with the MSI since each data has a value of 0.051, 0.252, and 0.215 respectively which is greater than the significance value of 0.05.