• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.157-160
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• 2006

웹 자원이 방대함에 따라, 사용자가 원하는 정보를 얼마나 정확하게 제시하느냐가 정보검색시스템 성능을 판단하는 기준이 된다. 그러나 동형이의어만을 질의어로 이용한 검색 결과는 동형이의어 각 의미에 관련된 문서가 혼재되어 있거나, 특정 의미에 관련된 문서가 집중적으로 나타나는 현상을 볼 수 있다. 이에 본 논문에서는 한국어 사용자 어휘지능망(U-WIN)의 관계정보를 이용하여 질의어의 모호성을 해결하고 의미적 정보검색의 기반을 마련하고자 한다. 우선, 전문분야에 주로 사용되는 동형이의어와 보편적으로 사용하는 동형의어를 구번하여 질의어로 선정하고, '질의어+상위어' 형태의 확장 질의어에 대해 두 개의 포탈사이트(Google, Naver)를 대상으로 웹 문서를 검색하여 정확률이 각각 81.5%(Naver), 65.5%(Google)로 나타났다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.187-189
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• 2005

인터넷 및 분산 환경에서 XML은 애플리케이션 간의 자료 저장 및 자료 교환을 위한 표준으로써, XML 문에 대한 연구가 활발히 진행되고 있다. 따라서 이기종 관계형 데이터베이스 시스템들 간의 메타데이터 및 데이터 교환을 위해 W3C에서 제안한 XML Schema를 사용한다. XML Schema는 평면적 구조인 관계형 데이터베이스 시스템의 메타데이터 및 데이터를 계층적 구조인 XML 문서형식으로 나타낼 수 있는 메커니즘을 가지고 있으며, 다양한 원시 데이터 형식을 지원하여 관계형 데이터베이스 시스템이 제공하는 데이터형식을 충분히 반영할 수 있는 구조를 가지고 있다. 또한 기존의 이질적인 전자상거래 플랫폼을 사용하므로 인해 발생하는 시스템간의 상호 호환 및 운영의 어려움이 있다. 그러나 분산 환경에서 이질적인 특성을 해결하기 위해서 XML을 기반으로 하는 쇼핑몰들의 통합된 정보를 검색할 수 있는 사이트가 등장하고 있어 고객들이 구매하고자 하는 상품에 대한 정보를 보다 쉽게 검색할 수 있도록 각종 쇼핑몰 사이트를 연결하여 통합하는 과정이 진행 중이다. 따라서 상품을 검색할 때 메타데이터를 이용하여 선택에 필요한 정보를 고객에게 제공함으로서 상품을 효율적으로 검색할 수 있다. 따라서 XML기반으로 분산된 이 기증의 시스템들을 온톨로지(Ontology)기반의 메타데이터를 이용하여 상품을 검색할 수 있는 시스템을 제안하고, 온톨로지 기반의 메타데이터 XMDR(eXtended MetaData Registry)을 이용한 상품 검색 시스템을 효율적으로 검색하기 위한 온톨로지 서버 구축에 관한 방법을 제안한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.674-677
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• 2004

This paper deals with a systematic approach for the construction of the fixed-delay tree search (FDTS) detector in the intersymbol interference channel. The approach is based on the efficient multi-dimensional space partitioning. The Voronoi diagram (VoD) and the Delaunay tessellation (DT) of the multi-dimensional space are applied to implement the algorithm. In the proposed approach, utilizing the geometric information contained in the VOD/DT, the relative location of the observation sequence is determined which has been shown to reduce the implementation complexity. Detailed construction procedures are discussed followed by an example from the intersymbol interference communication channel.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.2
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• pp.278-283
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• 2008

As the usefulness of internet is kept changing more productively with web 1.0, web 2.0 usage of XML is also increasing very rapidly. In XML environment the most critical function is the ability of effective retrieval of useful information from XML repository. That makes the W3C XQuery more popular XQuery has very complicated structure as a query language due to the semi_structured nature of XML. FLOWOR, which stand for, let. where, order by, return, is the most commonly used expression in XQuery. In this paper we suggest the methods to handle XQuery FLWOR on relational environments. We also analyze and evaluate our approach to prove its correctness.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.6
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• pp.808-813
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• 2008

u-City is a city for users who are in everywhere as well as everytime. Korea e-government portal as a main e-government portal is a gateway for entering Korea e-government, but it has some problems. This portal has to provide a simple interface according to user's needs, but the current system is too complicated so that this system does not provide information retrieval function according to user's needs. So in this paper, we propose an effective strategy and functions of Korea e-government main portal for effective u-City.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.367-374
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• 1999

This paper suggests an integrated method based on concept ascension and attribute reduction for efficient induction of decision rules from a large database. We study an automatic scheme to generate concept trees by a clustering technique, a method for generalizing databases by the concept ascension technique, an optimal reduction method by means of attributes reduction using the sibmificance of attributes, and an efficient way of reduction of attribute values applying the discernible matrix and functions. The method can be used for the decision making tasks such as an investment planning or price evaluation, the construction of knowledge bases for diagnosis of defects or medical diagnosis, data analysis such as marketing or experimental data, information retrieval for high level inquiries, and so on.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.389-398
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• 2007

Case-based reasoning (CBR) is one of the most popular prediction techniques for medical diagnosis because it is easy to apply, has no possibility of overfitting, and provides a good explanation for the output. However, it has a critical limitation - its prediction performance is generally lower than other artificial intelligence techniques like artificial neural networks (ANNs). In order to obtain accurate results from CBR, effective retrieval and matching of useful prior cases for the problem is essential, but it is still a controversial issue to design a good matching and retrieval mechanism for CBR systems. In this study, we propose a novel approach to enhance the prediction performance of CBR. Our suggestion is the simultaneous optimization of feature weights, instance selection, and the number of neighbors that combine using genetic algorithms (GAs). Our model improves the prediction performance in three ways - (1) measuring similarity between cases more accurately by considering relative importance of each feature, (2) eliminating redundant or erroneous reference cases, and (3) combining several similar cases represent significant patterns. To validate the usefulness of our model, this study applied it to a real-world case for evaluating cytological features derived directly from a digital scan of breast fine needle aspirate (FNA) slides. Experimental results showed that the prediction accuracy of conventional CBR may be improved significantly by using our model. We also found that our proposed model outperformed all the other optimized models for CBR using GA.

• Journal of the Korea Society of Computer and Information
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• v.16 no.7
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• pp.95-103
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• 2011

The actual utilization of Semantic Web technology which aims to provide more intelligent and automated service for information retrieval over the Web becomes gradually reality. RDF is widely used as the one of standard formats to present and manage the voluminous data on the Web. Efficient query processing on RDF data, therefore, is one of the ongoing research topics. Retrieving resources having a specific association from a given resource is the typical query processing type and several researches for this have done. However the most of previous researches have not fully considered discovering the complex relationship among resources such as returning the association between resources as the query processing result. This paper introduces the indexing and query processing for ${\rho}$-intersect operation which is one of the semantic association retrieval types. It includes an indexing scheme using suffix array and optimal processing approaches for handling ${\rho}$-intersect operation. The experimental evaluations shows that the average execution times for the proposed approach is 3~7 times faster than the previous approach.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.479-486
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• 2005

The ontology was proposed to construct the logical basis of semantic web. Ontology represents domain knowledge in the formal form and it enables that machine understand domain knowledge and provide appropriate intelligent service for user request. However, the construction and the maintenance of ontology requires large amount of cost and human efforts. This paper proposes an automatic ontology construction method for defining relation between concepts in the documents. The Proposed method works as following steps. First we find concept pairs which compose association rule based on the concepts in domain specific documents. Next, we find pattern that describes the relation between concepts by clustering the context between two concepts composing association rule. Last, find generalized pattern name by clustering the clustered patterns. To verify the proposed method, we extract relation between concepts and evaluate the result using documents set provide by TREC(Text Retrieval Conference). The result shows that proposed method cant provide useful information that describes relation between concepts.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.1-15
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• 2005

The explosive growth of the Internet leads to various on-line shopping malls and active E-Commerce. however, as the internet has experienced continuous growth, users have to face a variety and a huge amount of items, and often waste a lot of time on purchasing items that are relevant to their interests. To overcome this problem the comparison shopping systems, which can help to compare items' information with those other shopping malls, have been issued as a solution. However, when users do not have much knowledge what they want to find, a keyword-based searching in the existing comparison shopping systems lead users to waste time for searching information. Thereby, the performance is fell down. To solve this problem in this research, we suggest the Comparison Shopping System using Image Retrieval based on Semantic Web. The proposed system can assist users who don't know items' information that they want to find and serve users for quickly comparing information among the items. In the proposed system we use semantic web technology. We insert the Semantic Annotation based on Ontology into items' image of each shopping mall. Consequently, we employ those images for searching the items instead of using a complex keyword. In order to evaluate performance of the proposed system we compare our experimental results with those of Keyword-based Comparison Shopping System and simple Semantic Web-based Comparison Shopping System. Our result shows that the proposed system has improved performance in comparison with the other systems.