• Proceedings of the Korea Information Processing Society Conference
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• 2009.04a
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• pp.1017-1020
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• 2009

본 연구는 차세대 컴퓨터 패러다임의 지식베이스로 각광받는 온톨로지의 구축에 있어, 온톨로지가 실제 응용이나 서비스로 더욱 안정적으로 활용될 수 있는 온톨로지 평가를 위한 이론적 근거를 제시하는데 그 목적이 있다. 현재 많은 온톨로지가 구축되고 응용에 활용되기 위한 연구가 진행되나 이의 안정성과 유용성을 평가하기 위한 방법에 대한 연구는 부족한 상황이다. 따라서 본 연구는 소프트웨어공학적 측면에서 온톨로지의 소비자들이 만족할 수 있고 활용될 수 있는 온톨로지 구축을 위한 온톨로지를 평가하기 위한 서비스지향적 온톨로지 공학 기준과 온톨로지 평가 방안을 제시하고자 한다.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.7
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• pp.639-649
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• 2000

In the relational database systems, the join operation is one of the most time-consuming query operations. Many parallel join algorithms have been developed to reduce the execution time. Multiple hash join algorithm using allocation tree is one of most efficient ones. However, it may have some delay on the processing each node of allocation tree, which is occurred in tuple-probing phase by the difference between one page reading time of outer relation and the processing time of already read one. In this paper, to solve the performance degrading problem by the delay, we develop a join algorithm using the concept of 'synchronization of page execution time' for multiple hash joins. We reduce the processing time of each nodes in the allocation tree and improve the total system performance. In addition, we analyze the performance by building the analytical cost model and verify the validity of it by various performance comparison with previous method.

• Journal of KIISE:Databases
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• v.33 no.7
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• pp.682-692
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• 2006

Searching for gene products which have similar biological functions are crucial for bioinformatics. Modern day biological databases provide the functional description of gene products using Gene Ontology(GO). In this paper, we propose a technique for semantic similarity search for gene products using the GO annotation information. For this purpose, an information-theoretic measure for semantic similarity between gene products is defined. And an algorithm for semantic similarity search using this measure is proposed. We adapt Fagin's Threshold Algorithm to process the semantic similarity query as follows. First, we redefine the threshold for our measure. This is because our similarity function is not monotonic. Then cluster-skipping and the access ordering of the inverted index lists are proposed to reduce the number of disk accesses. Experiments with real GO and annotation data show that GORank is efficient and scalable.

• Journal of KIISE:Computer Systems and Theory
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• v.35 no.4
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• pp.158-165
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• 2008

LOINC (Logical Observation Identifiers Names and Codes) is a database and universal standard for identifying laboratory and clinical test results that is developed and maintained by Regenstrief Institute. Exchanging laboratory test results is one of the most important area in EHR system and the terminology for laboratory test results has to be standardized. In this paper, we present a pre-preprocessing tool that converts a local database in healthcare organizations to LMOF format LMOF format is required by RELMA and our work helps mapping laboratory test results to LOINC very efficiently Our proposed tool provided user friendly interface and 15% keyword reduction in RELMA search compared to no pre-processing RELMA search.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.9
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• pp.445-458
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• 2007

This article presents a novel infrastructure for large-memory database processing using commodity hardware with operating system support. We exploit inexpensive PCs and a high-speed network capable of Remote Direct Memory Access (RDMA) operations to build a new memory hierarchy between fast volatile memory and slow disk storage. The new memory hierarchy guarantees a reasonable response time, and its storage size enables us to run large-memory database systems with little performance degradation. The proposed architecture has two main components: (1) a remote memory system inside the Linux kernel to manage other computers' memory pages efficiently and (2) a remote memory pager responsible for manipulating remote read/write operations on remote memory pages. We insist that the proposed architecture is practical enough to support the rigorous demands of commercial in-memory database systems by demonstrating the performance of publicly available main-memory databases (e.g., MySQL) on our prototyped system. The experimental results show very interesting results from the TPC-C benchmark.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.555-565
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• 1999

The optimal identification algorithm of fuzzy systems is presented for rule-based fuzzy modeling of nonlinear complex systems. Nonlinear systems are expressed using the identification of structure such as input variables and fuzzy input subspaces, and parameters of a fuzzy model. In this paper, the rule-based fuzzy modeling implements system structure and parameter identification using the fuzzy inference methods and hybrid structure combined with two types of optimization theories for nonlinear systems. Two types of inference methods of a fuzzy model are the simplified inference and linear inference. The proposed hybrid optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Here, a genetic algorithm is utilized for determining initial parameters of membership function of premise fuzzy rules, and the improved complex method which is a powerful auto-tuning algorithm is carried out to obtain fine parameters of membership function. Accordingly, in order to optimize fuzzy model, we use the optimal algorithm with a hybrid type for the identification of premise parameters and standard least square method for the identification of consequence parameters of a fuzzy model. Also, an aggregate performance index with weighting factor is proposed to achieve a balance between performance results of fuzzy model produced for the training and testing data. Two numerical examples are used to evaluate the performance of the proposed model.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.545-557
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• 2001

In this paper we propose a hierarchical classification algorithm based on rough membership function which can reason a new object approximately. We use the fuzzy reasoning method that substitutes fuzzy membership value for linguistic uncertainty and reason approximately based on the composition of membership values of conditional sttributes Here we use the rough membership function instead of the fuzzy membership function It can reduce the process that the fuzzy algorithm using fuzzy membership function produces fuzzy rules In addition, we transform the information system to the understandable minimal decision information system In order to do we, study the discretization of continuous valued attributes and propose the discretization algorithm based on the rough membership function and the entropy of the information theory The test shows a good partition that produce the smaller decision system We experimented the IRIS data etc. using our proposed algorithm The experimental results with IRIS data shows 96%~98% rate of classification.

• Korean Journal of Cognitive Science
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• v.20 no.3
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• pp.335-355
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• 2009

We examined risk judgment and the accuracy of inference based on two kinds of probabilities in a Bayesian inference task: the death probability from a disease (base rates) and the probability of having a disease with positive results in the screening test (posterior probabilities). Risk information were presented in either a probability or a frequency format. In Study 1, we found a numerical format effect for both base rate and posterior probability. Participants rated information as riskier and inferred more accurately in the frequency condition than in the probability condition for both base rate and posterior probability. However, there was no frequency range effect, which suggested that the ranges of frequency format did not influence risk ratings. In order to find out how the analytic thought system influences risk ratings, we compared the ratings of a computation condition and those of a no-computation condition and still found the numerical format effect in computation condition. In Study 2, we examined the numerical format effect and frequency range effect in a high and a low probability condition and found the numerical format effect at each probability level. This result suggests that people feel riskier in the frequency format than in the probability format regardless of the base rates and the posterior probability. We also found a frequency range effect only for the low base rate condition. Our results were discussed in terms of the dual process theories.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.91-109
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• 2004

This study investigates the effectiveness of a hybrid approach using fuzzy sets that describe approximate phenomena of the real world. Compared to the other existing techniques, the approach handles inexact knowledge in common linguistic terms as human reasoning does it. Integration of fuzzy sets with case-based reasoning (CBR) is important in that it helps to develop a successful system far dealing with vague and incomplete knowledge which statistically uses membership value of fuzzy sets in CBR. The preliminary results show that the accuracy of the integrated fuzzy-CBR approach proposed for this study is higher that of conventional techniques. Our proposed approach is applied to corporate bond rating of Korean companies.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.79-92
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• 2002

This paper describes a research work of developing computer-aided design of a product with bending and piercing for progressive working. An approach to the system for progressive working is based on the knowledge-based rules. Knowledge for the system is formulated from plasticity theories, experimental results and the empirical knowledge of field experts. The system has been written in AutoLISP on the AutoCAD with a personal computer and is composed of four main modules, which are input and shape treatment, flat pattern layout, strip layout and die layout modules. The system is designed by considering several factors, such as bending sequences by fuzzy set theory, complexities of blank geometry, punch profiles, and the availability of a press equipment. Strip layout drawing generated in the strip layout module is presented in 3-D graphic farms, including bending sequences and piercing processes with punch profiles divided into for external area. The die layout module carries out die design for each process obtained from the results of the strip layout. Results obtained using the modules enable the manufacturer for progressive working of electric products to be more efficient in this field.