• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.6
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• pp.27-36
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• 1998

This paper suggests an integrated method based on rough sets for discovering useful knowledge from a large databse. Our approach applies attribute-oriented concept hierarchy ascension technique to extract generalized data from actual data in database, induction of decision trees to measure the information gain, and knowledge reduction method of rough set theory to remove superfluous attributes and attribute values. The integrated algorithm first reduces the size of database through the concept generalization, reduces the number of attributes by means of eliminating condition attributes which have little influence on decision attribute, and finally induces simplified decision rules by removing the superfluous attribute values by analyzing the dependency relationships among the attributes.

• Journal of Information Technology Services
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• v.11 no.2
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• pp.49-68
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• 2012

The purpose of this study is to analyse the country image, the pre-assessment, and the usage intention about overseas internet shopping mall service in china and how these factors are related to one another according to internet shopping mall using experience. And this study divided the country image for internet shopping mall service into two components : general country attribute and general service product attribute. In this study it is found that the country image of international internet shopping service is directly related to the pre-assessment, and the pre-assessment is related to usage intention especially in case that chinese consumer has a lot of internet shopping mall using experience. In the other case, the general country attributes affect the general service product attributes but the general service product attributes don't have any relationship with the pre-assessment. For a successful international internet shopping mall service business in China, marketer should recognize that it is important to formulate the policy extending the internet shopping mall experience as well as using the country image.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.764-772
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• 2003

The main thrust of our talk will be based on our experience in developing and applying an attribute-based classification technique in the context of an operational answer set driven retrieval system. To alleviate the difficulty and reduce the cost of manually constructing and maintaining answer sets, i.e., knowledge base, we have devised a new method of automating the answer document selection process by using the notion of attribute-based classification, which is in and of itself novel. We attempt to explain through experiments how helpful the proposed method is for the knowledge base construction process.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.275-284
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• 2008

The digital map needs efficiently updating. Because it is a base map at each local government and several geographic information systems and that is the key to enhancing to use spatial data. We suggest the linking method of building registers to the building layers of digital map, to update attribute data of the building layers. To conduct that, it is very important that each building in two data is linked by one-to-one matching. In this paper, we generate the strategy for renewing attribute data of the building layers based on identifier by using identifier of the new address system.

• KIISE Transactions on Computing Practices
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• v.22 no.8
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• pp.345-350
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• 2016

Cloud computing services have different characteristics from the traditional computing environment such as resource sharing, virtualization, etc. These characteristics of cloud computing environment necessitate specific properties such as user identify, access control, security control property, etc. Recently, Yoo proposed an attribute-based authentication scheme for secure cloud computing. However, Yoo's authentication scheme is vulnerable to customer attack and an adversary can modify the authentication request message. In this paper, we propose a secure and efficient attribute-based authentication scheme for cloud computing based on Yoo's scheme.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.883-889
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• 2009

The importance of cost estimate in early stage such has been increasing due to market change and severe competition in construction industry. Because the adjustable budget is only 20% after design stage, most of the crucial decisions to influence cost is made in the early stage. However, in the early stage, the project scope is not defined completely so that estimator has inaccurate information to make critical decision. Therefore, this research suggests the cost estimate method using case-based reasoning. Case-based reasoning is appropriate for the early cost estimating, as it has the strength of rapidity and convenience in cost estimation. This research analyzes 84 actual data of public apartment on the scale of 11~15 stories. In order to extract the most similar case, at the first step this research identifies influence factors and calculates attribute similarity. In case-based reasoning, the most challenging task is determining attribute weight. At the third step, this research calculates case similarity which is aggregated attribute similarity multipled by attribute weight. Finally, extracts the most similar case which has the highest score of case similarity.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.394-405
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• 2001

Since most real-world application data involve continuous-valued attributes, properly addressing the discretization process for constructing a decision tree is an important problem. A continuous-valued attribute is typically discretized during decision tree generation by partitioning its range into two intervals recursively. In this paper, by removing the restriction to the binary discretization, we present a hybrid multi-interval discretization algorithm for discretizing the range of continuous-valued attribute into multiple intervals. On the basis of experiment using semiconductor etching machine, it has been verified that our discretization algorithm constructs a more efficient incremental decision tree compared to previously proposed discretization algorithms.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.169-182
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• 2011

Privacy preserving microdata publication has received wide attention. In this paper, we investigate the randomization approach and focus on attribute disclosure under linking attacks. We give efficient solutions to determine optimal distortion parameters, such that we can maximize utility preservation while still satisfying privacy requirements. We compare our randomization approach with l-diversity and anatomy in terms of utility preservation (under the same privacy requirements) from three aspects (reconstructed distributions, accuracy of answering queries, and preservation of correlations). Our empirical results show that randomization incurs significantly smaller utility loss.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.97-102
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• 2022

Network intrusion detection is becoming an increasing necessity for both organizations and individuals alike. Detecting intrusions is one of the major components that aims to prevent information compromise. Automated systems have been put to use due to the voluminous nature of the domain. The major challenge for automated models is the noise and data imbalance components contained in the network transactions. This work proposes an ensemble model, Attribute Subset Selector Bagging (ASUB) that can be used to effectively handle noise and data imbalance. The proposed model performs attribute subset based bag creation, leading to reduction of the influence of the noise factor. The constructed bagging model is heterogeneous in nature, hence leading to effective imbalance handling. Experiments were conducted on the standard intrusion detection datasets KDD CUP 99, Koyoto 2006 and NSL KDD. Results show effective performances, showing the high performance of the model.

• Journal of applied mathematics & informatics
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• v.41 no.6
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• pp.1377-1391
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• 2023

When sensitive topics such as gambling habits, drug addiction, alcoholism, tax evasion tendencies, induced abortions, drunk driving, past criminal involvement, and homosexuality are the focus of open or direct surveys, it becomes challenging to obtain accurate information due to nonresponse bias and response bias. People often hesitate to provide truthful answers. Warner introduced an ingenious method to address this issue. In this study, a new and unrelated randomized response model is proposed to eliminate misleading responses and nonresponses caused by the stigma associated with the attribute being investigated. The proposed randomized response model allows for the estimation of the population percentage with the sensitive characteristic in an unbiased manner. The characteristics and recommendations of the proposed randomized response model are examined, and numerical examples are provided to support the findings of this study.