• Journal of Computing Science and Engineering
• /
• v.5 no.3
• /
• pp.183-196
• /
• 2011

There has recently been a surge of interest in relational database mining that aims to discover useful patterns across multiple interlinked database relations. It is crucial for a learning algorithm to explore the multiple inter-connected relations so that important attributes are not excluded when mining such relational repositories. However, from a data privacy perspective, it becomes difficult to identify all possible relationships between attributes from the different relations, considering a complex database schema. That is, seemingly harmless attributes may be linked to confidential information, leading to data leaks when building a model. Thus, we are at risk of disclosing unwanted knowledge when publishing the results of a data mining exercise. For instance, consider a financial database classification task to determine whether a loan is considered high risk. Suppose that we are aware that the database contains another confidential attribute, such as income level, that should not be divulged. One may thus choose to eliminate, or distort, the income level from the database to prevent potential privacy leakage. However, even after distortion, a learning model against the modified database may accurately determine the income level values. It follows that the database is still unsafe and may be compromised. This paper demonstrates this potential for privacy leakage in multi-relational classification and illustrates how such potential leaks may be detected. We propose a method to generate a ranked list of subschemas that maintains the predictive performance on the class attribute, while limiting the disclosure risk, and predictive accuracy, of confidential attributes. We illustrate and demonstrate the effectiveness of our method against a financial database and an insurance database.

• Proceedings of the IEEK Conference
• /
• 2002.06e
• /
• pp.273-276
• /
• 2002

This paper has design of ECG pattern classification system using decision of fuzzy IF-THEN rules and neural network. each fuzzy IF-THEN rule in our classification system has antecedent lingustic values and a single consequent class. we use a fuzzy reasoning method based on a single winner rule in the classification phase. this paper in, the MIT/BIH arrhythmia database for the source of input signal is used in order to evaluate the performance of the proposed system. From the simulation results, we can effectively pattern classification by application of learned from neural networks.

• Nuclear Engineering and Technology
• /
• v.34 no.6
• /
• pp.610-618
• /
• 2002

A study of the conceptual data modeling to realize the decommissioning database on the HRR-1&2 was carried out. In this study, the current state of the abroad decommissioning database was investigated to make a reference of the database. A scope of the construction of decommissioning database has been set up based on user requirements. Then, a theory of the database construction was established and a scheme on the decommissioning information was classified . The facility information, work information, radioactive waste information, and radiological information dealing with the decommissioning database were extracted through interviews with an expert group and also decided upon the system configuration of the decommissioning database. A code which is composed of 17 bit was produced considering the construction, scheme and information. The results of the conceptual data modeling and the classification scheme will be used as basic data to create a prototype design of the decommissioning database.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.23 no.4
• /
• pp.1045-1050
• /
• 1998

Classification techniques are often an importand component of intelligent systems and are use for both deta preprocessing and decision making. In the design of a classification system, the labled samples must be given to provide a priori information for the classification. Moreover, the number of classes to be categorized must be known a priori information, called OFCAM. In OFCAM, an unsupervised by OFCAM, the database of a classification system, called PCSDB, is constructed. Then, PCSDB can be effectively used in the decision process of the system.

• Journal of the Society of Disaster Information
• /
• v.13 no.3
• /
• pp.322-331
• /
• 2017

This study proposed subway construction information classification system based on civil engineering information classification system proposed by Korea Institute of Construction Technology. Also, Based on this criterion, This study established data modeling for NAS operating system Composed of construction information classification system - network - operation and presented an relational database integrated model. The data modeling method proposed in this study can be applied to other civil engineering facilities, so it can be operated as scientific NAS.

• Journal of Korea Multimedia Society
• /
• v.25 no.1
• /
• pp.135-143
• /
• 2022

In order to convert Korean folk paintings called Minhwa, a part of traditional Korean heritage, into DBs, it is necessary to design a classification system suitable for the characteristics of folk paintings. A classification system and the generating of unique codes are required to classify and save them. To realize this, a basic classification system was created by listing objects depicted in folk paintings, and keywords were extracted by reclassifying them for each object. In order to assign a unique code to each piece, we organize the English names of each Minhwa since the English names of the folk painting contain the names of objects. The code name is extracted by applying the order of nouns and consonant priority rules in English names and attaching five Arabic numerals. These codes are later assigned to each image file stored in the database and are input together with the keyword. The Minhwa DB constructed in this way enables storage and search centered on objects and keywords and the intuitive inferring of the type of object from the code name.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.766-771
• /
• 2008

In this paper, we propose a system of mimicking image classification for building database system. It better manages the format which recording the same advertisements multimedia in advertisements image. Recently, the work of converting database is made directly by the people. This work doses the media scanning, image editing and saving, and saving of advertising information (date, the media, the page and size, so far). Therefore, it is wasted a lot of time and manpower as inefficient business. To solve these problems, first of all we gain an image by digital camera, extract and classify candidate area of advertisements. Accordingly, our system saves database to comparison of the mimicking of all advertising and classify whether area of image is the new or existing advertising.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.21 no.11
• /
• pp.2052-2060
• /
• 2017

The SOLAS ship should carry at least 83 different types of equipment based on the SFI group codes and each of which consists of several to dozens of components. During ship operation, it is necessary to ensure the normal operation of such equipment, and remote maintenance is highly demanded for immediate repair in the event of a equipment fault. This study proposes to find suitable classification system and to derive database structure for remote maintenance of navigation and communication equipment. As a result of this study, the classification system of equipment should be layered into equipment type, model, and component, and main table in the database consists of FMEA, service history, case data through Q&A, Preventive Maintenance. A database was constructed for 140 navigation and communication equipment models and 750 components. In order to evaluate the practical effects, service engineer evaluated the usefulness using the cloud app.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.6 no.2
• /
• pp.167-174
• /
• 2002

Earth retaining structure is constructed structure in order to construct a multistoried building, the subway, a subterranean downtown for effective use and obtainments of the limited ground. Recently, many kinds of research have been actively developed for a standardization and a database on designing and constructing of bridge, tunnel, road. With the works of database construction of that, many kinds of data with respect to statistics is cumulated. However, Database work of designed and constructed earth retaining structure in the construction field is wholly lacking and lagged behind in the works of database construction. This paper suggested classification system on indication data in connection with designing and constructing earth retaining structures a hundred fields. On the basis of that, code work with classification system was practised and DB program of indication data in connection with designing and constructing earth retaining structures was developed.

• Proceedings of the KSRS Conference
• /
• v.2
• /
• pp.706-709
• /
• 2006

Cancer is one of the major causes of death; however, the survival rate can be increased if discovered at an early stage for timely treatment. According to the statistics of the World Health Organization of 2002, breast cancer was the most prevalent cancer for all cancers occurring in women worldwide, and it account for 16.8% of entire cancers inflicting Korean women today. In order to classify the type of breast cancer whether it is benign or malignant, this study was conducted with the use of the discriminant analysis and the decision tree of data mining with the breast cancer data disclosed on the web. The discriminant analysis is a statistical method to seek certain discriminant criteria and discriminant function to separate the population groups on the basis of observation values obtained from two or more population groups, and use the values obtained to allow the existing observation value to the population group thereto. The decision tree analyzes the record of data collected in the part to show it with the pattern existing in between them, namely, the combination of attribute for the characteristics of each class and make the classification model tree. Through this type of analysis, it may obtain the systematic information on the factors that cause the breast cancer in advance and prevent the risk of recurrence after the surgery.