• Asia pacific journal of information systems
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• v.4 no.1
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• pp.115-138
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• 1994

Current database systems are based on the assumption that a datum denotes the same meaning; however, in reality, the violation of this assumption is not unusual. Some data are created in such a way that they represent different sets of attribute values. The current research formulates this phenomenon as dissimilarities of derivation rules and defines multi-derived data as ones that are derived by multiple rules. For multi- derived data, this research proposes a new retrieval scheme and analyze its implication with relation to data retrieval.

• Journal of Sensor Science and Technology
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• v.15 no.6
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• pp.433-441
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• 2006

Because of the low power and low rate of a sensor network, outlier is frequently occurred in the time series data of sensor network. In this paper, we suggest periodic pattern analysis that is applied to the time series data of sensor network and predict outlier that exist in the time series data of sensor network. A periodic pattern is minimum period of time in which trend of values in data is appeared continuous and repeated. In this paper, a quantization and smoothing is applied to the time series data in order to analyze the periodic pattern and the fluctuation of each adjacent value in the smoothed data is measured to be modified to a simple data. Then, the periodic pattern is abstracted from the modified simple data, and the time series data is restructured according to the periods to produce periodic pattern data. In the experiment, the machine learning is applied to the periodic pattern data to predict outlier to see the results. The characteristics of analysis of the periodic pattern in this paper is not analyzing the periods according to the size of value of data but to analyze time periods according to the fluctuation of the value of data. Therefore analysis of periodic pattern is robust to outlier. Also it is possible to express values of time attribute as values in time period by restructuring the time series data into periodic pattern. Thus, it is possible to use time attribute even in the general machine learning algorithm in which the time series data is not possible to be learned.

• Journal of Korean Society for Quality Management
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• v.39 no.1
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• pp.57-70
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• 2011

The paper presents the results of a study on the determinants of customer satisfaction for a retail bank using the data of 2009 NCSI(National Customer Satisfaction Index, KPC). In doing so, it uses a revised version of the traditional analyses based on derived measures of attribute importance. The need for a revised methodology is prompted by the insights of the two- and three-factor theories of customer satisfaction, such as Kano's framework. Indeed, the evidence from 1635 customers of 6 Korean banks confirms an asymmetric relationship between attribute performances and overall customer satisfaction. The results from both a traditional and our revised approach are compared. While this approach can be applied across different industries, it should not be assumed that the numerical results presented in the paper apply to contexts with substantially different underlying characteristics. General trends and practical implications for banking services are reported in the conclusions.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.4
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• pp.413-420
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• 2011

This study is to extract landmark buildings for pedestrian navigation from the existing spatial data sets automatically. At first, we defined candidates for landmark based on sight of pedestrian, then extracted final landmark by evaluating attributes of each candidate. The attribute is evaluated with relative or absolute criteria depending on the nature of each attribute. Landmarks extracted through the proposed method are compared to existing landmarks for vehicle and assessment of the validity and the applicability is performed. As a result, extracted Landmarks are expected to help guiding pedestrian effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.5
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• pp.1343-1356
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• 2013

Cloud computing has emerged as perhaps the hottest development in information technology at present. This new computing technology requires that the users ensure that their infrastructure is safety and that their data and applications are protected. In addition, the customer must ensure that the provider has taken the proper security measures to protect their information. In order to achieve fine-grained and flexible access control for cloud computing, a new construction of hierarchical attribute-based encryption(HABE) with Ciphertext-Policy is proposed in this paper. The proposed scheme inherits flexibility and delegation of hierarchical identity-based cryptography, and achieves scalability due to the hierarchical structure. The new scheme has constant size ciphertexts since it consists of two group elements. In addition, the security of the new construction is achieved in the standard model which avoids the potential defects in the existing works. Under the decision bilinear Diffie-Hellman exponent assumption, the proposed scheme is provable security against Chosen-plaintext Attack(CPA). Furthermore, we also show the proposed scheme can be transferred to a CCA(Chosen-ciphertext Attack) secure scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1832-1853
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• 2018

The personal health record (PHR) system is a promising application that provides precise information and customized services for health care. To flexibly protect sensitive data, attribute-based encryption has been widely applied for PHR access control. However, escrow, exposure and abuse of private keys still hinder its practical application in the PHR system. In this paper, we propose a coordinated ciphertext policy attribute-based access control with user accountability (CCP-ABAC-UA) for the PHR system. Its coordinated mechanism not only effectively prevents the escrow and exposure of private keys but also accurately detects whether key abuse is taking place and identifies the traitor. We claim that CCP-ABAC-UA is a user-side lightweight scheme. Especially for PHR receivers, no bilinear pairing computation is needed to access health records, so the practical mobile PHR system can be realized. By introducing a novel provably secure construction, we prove that it is secure against selectively chosen plaintext attacks. The analysis indicates that CCP-ABAC-UA achieves better performance in terms of security and user-side computational efficiency for a PHR system.

• Journal of Information Technology Services
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• v.12 no.3
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• pp.23-37
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• 2013

Social commerce is a subset of e-commerce that involves using social media, and user contributions to assist in the online buying and selling of products and services. Given the rapid growth of social commerce sites such as Groupon, Ticketmonster, and Coupang, it has become critical to understand customer purchasing decision-making processes in the social commerce environment. This study developed a theoretical model to examine the role of social commerce site's stickiness in customers' repurchasing decision processes. This study identifies price attribute, variety of selection, shopping enjoyment, and anger as the key factors of social commerce site's stickiness. Data collected from 164 users who had more purchasing experiences with social commerce for more than 7 months were empirically tested against the research model. The analysis results indicate that social commerce site's stickiness plays an important role in enhancing customer's purchasing behavior. Moreover, price attribute and shopping enjoyment significantly influence social commerce site's stickiness, whereas anger does not significantly affect consumer purchasing decision-making processes. However, contrary to our expectation, variety of selection negatively influences social commerce site's stickiness. The theoretical and practical implications of the findings are described.

• Journal of Distribution Science
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• v.16 no.3
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• pp.13-21
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• 2018

Purpose - This study examined the effect of the importance of selective attribute of HMR(Home Meal Replacement) on customers' satisfaction and repurchase intention which is rapidly increasing with the changes of demographic, social and cultural trends as well as the influence of on and offline shopping channel moderating role. Research design, data, and methodology - Based on the research of previous studies, it assumed the selection attributes of HMR products were price, convenience, menu, freshness. With 231 surveyed questionnaires, this study was conducted by AMOS 21.0 and the SEM(structural equation model) was used as statistical method for examining the hypotheses in this study. Results - The analysis showed that price, convenience, and freshness had a significant effect on satisfaction, whereas menu did not affect satisfaction and the effect of satisfaction on repurchase intention was statistically significant. However, the results were different depending on the on and offline shopping channel for customers to buy HMR products. Price, menu and freshness are affected by online shopping, meanwhile convenience is more influenced by offline. Conclusions - This study analyzed the effect of selection attribute of HMR products on the satisfaction, repurchase intention, and the influence of each shopping channel, and provided practical implications.

• Journal of the Korean Home Economics Association
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• v.39 no.10
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• pp.55-67
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• 2001

The purpose of this study were 1) to find out the benefits sought factors and segment the customers of internet shopping mall, 2) to find out the store image factors of internet shopping mall, and 3) to analyze the internet shopping mall market using perceptual map of segmented groups. The questionnaires dealing with attribute dimension of internet shopping mall image, benefits sought, and demographic variables were selected from the previous studies or were developed for this study. The data from 319 respondents which were collected through the internet survey site was analyzed by factor analysis, cluster analysis, one-way ANOVA, and $X^2$-test. The results of this study were as follows: 1. Benefit sought by consumer in internet shopping malls was found to include six different factors: assortments of products, search efficiency, brand/fashionability, delivery convenience, promotion service and informativeness. 2. As a result of subdividing the consumers, four distinctive groups were formed on the basis of benefit factors: multi-benefit oriented group, convenience oriented group, brand oriented group and low-benefit oriented group. Demographic traits such as education and income level were proven to significantly differentiate the benefit segments. 3. In the structural components of internet shopping-malls image, product/information, service/convenience and economy were drawn from attribute dimensions. 4. 12 perceptual maps of internet shopping mall image were constructed and each ideal vector were drawn.

• The Research Journal of the Costume Culture
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• v.11 no.2
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• pp.193-207
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• 2003

The purpose of this study was to investigate the demographics and general clothing buying behavior according to clothing shopping orientation of female workers. A questionnaire was developed to measure clothing shopping orientation, fashion information sources, stores selection criteria, clothing purchasing frequency of a year, purchasing expenditure of clothing, the demographics. The questionnaire was administered to 775 female teacher in Chonnam. The data was analyzed using percentage, frequency, mean, factor analysis, Cluster Analysis, x 1_test and ANOVA, Duncan test. The results of the study were as follows: 1. The female teachers were classified into four groups by the cluster analysis; indifferent shopping group, rational shopping group, conspicuous shopping group, recreational shopping group. 2. In the case of purchasing motives, significant differences were found according to shopping orientation subdivision in four factors. 3. The evaluation criteria of product were significantly different depending on shopping orientation subdivision in practical attribute, socio-psychological attribute, and aesthetic attribute. 4. The significant differences were found according to shopping orientation subdivision in general clothing purchasing behavior(purchasing price range of clothing, clothing purchasing frequency of a year, method of payment, number of stores visited, experience of buying in the import brand)