• Proceedings of the Korean Information Science Society Conference
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• 2006.10c
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• pp.51-55
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• 2006

시맨틱 웹은 현재 웹의 확장된 개념으로 사람뿐만 아니라 컴퓨터 스스로가 데이터를 이해하고 처리할 수 있도록 정보에 의미를 부여하는 것이다. 시맨틱 웹 데이터를 기술하는 RDF를 통해 메타데이터를 표현하고 의미론적 추론이 가능하게 되었다. 따라서 기존에 일반 사용자가 쉽게 사용할 수 있는 키워드 검색 방법을 시맨틱 웹 데이터인 RDF/RDF 스키마에 적용함으로써 차세대 웹으로 인식되고 있는 시맨틱 웹을 일반 사용자도 쉽게 활용할 수 있도록 한다. 본 논문에서는 RDF 문서의 효율적인 검색을 위해 RDF 인스턴스와 RDF 스키마 정보를 저장하고, 키워드, 속성, 클래스 타입의 복합 조건 검색을 만족시키는 키워드 인덱스와 스키마 테이블 구조를 제안한다. 본 논문에서 제안한 구조는 다양한 조건들을 만족하는 리소스 정보의 빠르고 정확한 검색이 가능하도록 한다.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.1-15
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• 2007

Recently, semantic web technology, represented by ontology building, is being combined with web services technology, creating 'Semantic Web Services' as a new promising field in information retrieval research. Accordingly, many brokering and matchmaking agents are being developed and used in the field. However, literature review revealed that most models do not take QoS(Quality of Services) into consideration. In this study, a QoS-augmented matchmaking algorithm is developed based on service availability, response time, maximum transaction amount, reliability, accessibility and price as critical QoS items. A prototype for Intelligent Semantic Web Services System is developed using publicly available data. Performance test was conducted and reported at the end.

• Journal of Satellite, Information and Communications
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• v.7 no.3
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• pp.86-93
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• 2012

In this paper, we propose keyword search and ranking methods for OWL documents that describe metadata and ontology on the Semantic Web. The proposed keyword search method defines a unit of keyword search result as an information resource and expands a scope of query keyword to names of class and property or literal data. And we reflected derived information by inference in the keyword search by considering the elements of OWL documents such as hierarchical relationship of classes or properties and equal relationship of classes. In addition, our method can search a large number of information resources that are relevant to query keywords because of information resources indirectly associated with query keywords through semantic relationship. Our ranking method can improve user's search satisfaction because of involving a variety of factors in the ranking by considering the characteristics of OWL. The proposed methods can be used to retrieve digital contents, such as broadcast programs.

• The KIPS Transactions:PartC
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• v.13C no.1 s.104
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• pp.129-136
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• 2006

Information Retrieval System aims towards providing fast and accurate information to users. However, current search systems are based on plain svntactic analysis which makes it difficult for the user to find the exact required information. This paper proposes the SW-IRS (Semantic Web-based Information Retrieval System) using an Ontology Server. The proposed system is purposed to maximize efficiency and accuracy of information retrieval of unstructured and semi-structured documents by using an agent-based automatic classification technology and semantic web based information retrieval methods. For interoperability and easy integration, RDF based repository system is supported, and the newly developed ranking algorithm was applied to rank search results and provide more accurate and reliable information. Finally, a new ranking algorithm is suggested to be used to evaluate performance and verify the efficiency and accuracy of the proposed retrieval system.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.147-151
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• 2013

On retrieving high frequency keywords in information retrieval system, mismatchings to user's request are problems because of the various meanings of keywords in the existing ontology configuration. In this paper, it is to construct personnel selection ontology and rules in personnel management which are composed of various concepts and knowledges based on semantic web technology and suggest selection procedures to support these rules and knowledge retrieval system to verify suitability of selection results. This system utilizes a method of extraction of speech features by using non-parametric correlation coefficient. This proposed method has been validated by showing that the result average SNR of the experiment evaluation of the proposed techniques was shown to be decreased by .752dB.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.687-692
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• 2016

Conventional way to search documents is keyword-based queries using vector space model, like tf-idf. Searching process of documents which is based on keywords can make some problems. it cannot recogize the difference of lexically different but semantically same words. This paper studies a scheme of document search based on document queries. In particular, it uses centrality vectors, instead of tf-idf vectors, to represent query documents, combined with the Word2vec method to capture the semantic similarity in contained words. This scheme improves the performance of document search and provides a way to find documents not only lexically, but semantically close to a query document.

• The Journal of Society for e-Business Studies
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• v.15 no.3
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• pp.131-145
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• 2010

Until now, popular paradigms to provide e-catalog documents that are adapted to users' needs are keyword search or collaborative filtering based recommendation. Since users' queries are too short to represent what users want, it is hard to provide the users with e-catalog documents that are adapted to their needs(i.e., queries and preferences). Although various techniques have beenproposed to overcome this problem, they are based on index term matching. A conventional Bayesian belief network-based approach represents the users' needs and e-catalog documents with their corresponding concepts. However, since the concepts are the index terms that are extracted from the e-catalog documents, it is hard to represent relationships between concepts. In our work, we extend the conventional Bayesian belief network based approach to represent users' needs and e-catalog documents with a concept network which is derived from the Web directory. By exploiting the concept network, it is possible to search conceptually relevant e-catalog documents although they do not contain the index terms of queries. Furthermore, by computing the conceptual similarity between users, we can exploit a semantic collaborative filtering technique for recommending e-catalog documents.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.100-104
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• 2010

Recently with advent of Web 2.0, RESTful Web Services are becoming increasing trend to emphasize Web as platform. There are already many services and the number of service increases in very fast pace. So it is difficult to find the service what we want by keyword based search. To solve this problem, we developed the search method using sem antic technologies about RESTful Web Services. For that, first we define the system structure and model the description format based on the integrated search system for OpenAPIs, and then we add Semantic Markup (tagging, semantic annotation) on the HTML description pages. Next we extract RDF document from them and store it in service repository. Based on the keywords that are extended by means of ontology, the developed system provides more purified and extended results than similarity-based keyword searching system.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.351-357
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• 2013

Information retrieval by query keywords have some mismatching problems to fit user's requirement for the retrieved documents due to the varieties of users. These problems are originated from the different situations and characteristics of user's requirement. Also, it has a problem that general correlation coefficients did not display the information relations. In this thesis, it is to suggest knowledge retrieval system to verify feasibility of personnel selection procedure and results supporting selection rules after construction of personnel selection ontologies and rules composed of various concept and knowledge based on the semantic web technology. In the suggested system, it is to clear disadvantages of limited information retrieval providing the suitable information to satisfy user's different situations and characteristics using Spearman's coefficients. Experimental results by this semantic-based information retrieval show 90.3% of accuracy and 71.8% of recall compared with legacy keyword information retrieval.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.163-165
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• 2006

차세대 웹을 표현하는 단어로 XML(extensible markup language)과 시맨틱 웹(Semantic Web)을 꼽을 수 있다. XML은 1996년 W3C (World Wide Consortium)에서 제안한 데이터 표현 능력이 높은 언어이며, 시맨틱 웹은 사람이 읽고 해석하기에 편한 현재의 웹 대신에 컴퓨터가 이해할 수 있는 형태의 새로운 언어로 표현해 기계들끼리 서로 의사소통을 할 수 있는 지능형 웹을 말하는 것으로써 현재 XML을 기반으로 하는 RDF(Resource Description Framework)나 온톨로지 기술을 통해 시맨틱 웹 구축방안에 관한 연구가 활발히 진행되고 있다. 본 논문에서는 차세대 웹에서의 정보 공유를 위한 검색 에이전트의 역할 및 에이전트간의 구조에 관한 설명, XML&RDF 검색 에이전트의 설계 모델 및 현재까지 구현된 시스템의 개요를 보여준다.