• Journal of KIISE:Databases
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• v.35 no.3
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• pp.243-256
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• 2008

With rapid growth of Internet, the amount of information in the Web is increasing exponentially. However, information on the current Web is understandable only for human, and thus it makes the exact information retrieval difficult. For solving this problem, the Semantic Web is suggested and we must use ontology languages that can endow data to semantics for implementing it. One of the representative ontology languages is OWL(Web Ontology Language) adopted as a recommendation by the World-Wide Web Consortium. OWL has richer expression power and formal semantics than other ontology languages such as RDF and RDF-S. In addition, OWL includes hierarchical structure information between classes or properties. Therefore, an efficient OWL storage model considering hierarchical structure for effective information retrieval on the Semantic Web is required. In this paper, we suggest the XPOS(XPath-based OWL Storage) model including hierarchy information between classes or properties as XPath form and enabling intuitive and effective information retrieval. Also, we show the comparative evaluation results on the performance of XPOS model, Sesame, and the XML storage-based storage model regarding query processing.

• Journal of KIISE:Databases
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• v.35 no.2
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• pp.155-168
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• 2008

This paper proposes a relational security model-based RDF Web ontology access control model. The Semantic Web is recognized as a next generation Web and RDF is a Web ontology description language to realize the Semantic Web. Much effort has been on the RDF and most research has been focused on the editor, storage, and inference engine. However, little attention has been given to the security issue, which is one of the most important requirements for information systems. Even though several researches on the RDF ontology security have been proposed, they have overhead to load all relevant data to memory and neglect the situation that most ontology storages are being developed based on relational database. This paper proposes a novel RDF Web ontology security model based on relational database to resolve the issues. The proposed security model provides high practicality and usability, and also we can easily make it stable owing to the stability of the relational database security model.

• Journal of KIISE:Databases
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• v.32 no.6
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• pp.593-602
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• 2005

Need for machine-understandable web (Semantic web) is increasing in order for users to exactly understand Web information resources and currently there are two main approaches to solve the problem. One is the Topic map developed by the ISO/IEC JTC 1 and the other is the RDF (Resource Description Framework), one of W3C standards. Semantic web supports all of the metadata of the Web information resources, thus the necessity of interoperability between the Topic map and the RDF is required. To address this issue, several conversion methods have been proposed. However, these methods have some problems such as loss of meanings, complicated structure, unnecessary nodes, etc. In this paper, a new method is proposed to resolve some parts of those problems. The method proposed is called NOWL (NO structural Warp and semantics Loss). NOWL method gives several contributions such as maintenance of the original a Topic map instance structure and elimination of the unnecessary nodes compared with the previous researches.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.17-22
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• 2023

This study analyzed the genres of popular character web dramas and studied the development of story recommendations through the language model GPT. As a result of the study, it was confirmed that similar cliches are repeated in web dramas. In this study, a common story structure (cliché) was analyzed and a typical story structure was standardized and presented so that even unskilled video producers can easily produce character web dramas. For analysis, clichés of web dramas in the school romance genre, which is the most popular genre among teenagers, were listed in order of success. In addition, this study studied the story recommendation mechanism for users by learning the clichés that were analyzed and cataloged in GPT. Through this study, it is expected to accelerate the production of various contents as well as popular popularity through the acceptance of various databases from the standpoint of database consumption theory of web contents.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.249-277
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• 2023

The purpose of this study is to explore the potential contribution of citation metrics to improving the search performance of citation index databases. To this end, the study generated ten queries in the field of library and information science and conducted experiments based on the relevance assessment using 3,467 documents retrieved from the Web of Science and 60,734 documents published in 85 SSCI journals in the field of library and information science from 2000 to 2021. The experiments included re-ranking of the top 100 search results using citation metrics and search methods, query expansion experiments using vector space model retrieval systems, and the construction of a citation-based re-ranking system. The results are as follows: 1) Re-ranking using citation metrics differed from Web of Science's performance, acting as independent metrics. 2) Combining query term frequencies and citation counts positively affected performance. 3) Query expansion generally improved performance compared to the vector space model baseline. 4) User-based query expansion outperformed system-based. 5) Combining citation counts with suitability documents affected ranking within top suitability documents.

• Journal of Life Science
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• v.14 no.6 s.67
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• pp.991-996
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• 2004

This paper deals with an integrated system that facilitates researchers to do motif and domain search effectively and systematically. The system we developed is constructed on the basis of the integration of various resources related to motif, domain, and protein family. Those resources that can be classified into databases and search programs are dispersed to be available in Internet. In order to develop this system, we extracted core contents of diverse databases, which are required to analyze the protein function in terms of motifs or domains, to construct local databases and installed motif or domain search programs on our server, which corresponding database has as its own search program. Diverse utilities and CGI (Common Gateway Interface) programs make the databases and the search programs interlocked and web-based graphical user interfaces integrate all the components of our system. Employing our integrated system, end-users can receive its one-stop service to do protein function analysis systematically and effectively, without surfing many sites in Internet and wasting time over integrating search results.

• The Journal of Korean Association of Computer Education
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• v.8 no.6
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• pp.113-121
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• 2005

Since documents on the Web are naturally partitioned into many document databases, the efficient information retrieval (IR) process requires identifying the document databases that are most likely to provide relevant documents to the query and then querying the identified document databases. We first introduce a neural net agent for such an efficient IR, and then propose the hierarchically organized multi-agent IR system in order to scale our agent with the large number of document databases. In this system, the hierarchical organization of neural net agents reduced the total training cost at an acceptable level without degrading the IR effectiveness in terms of precision and recall. In the experiment, we introduce two neural net IR systems based on single agent approach and multi-agent approach respectively, and evaluate the performance of those systems by comparing their experimental results to those of the conventional statistical systems.

• Nuclear Engineering and Technology
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• v.42 no.4
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• pp.339-364
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• 2010

Following a joint OECD/NEA-IAEA-sponsored meeting to define the current role and future perspectives of the application of Computational Fluid Dynamics (CFD) to nuclear reactor safety problems, three Writing Groups were created, under the auspices of the NEA working group WGAMA, to produce state-of-the-art reports on different aspects of the subject. The work of the second group, WG2, was to document the existing assessment databases for CFD simulation in the context of Nuclear Reactor Safety (NRS) analysis, to gain a measure of the degree of quality and trust in CFD as a numerical analysis tool, and to take initiatives to extend the existing databases. The group worked over the period of 2003-2007 and produced a final state-of-the-art report. The present paper summarises the material gathered during the study, illustrating the points with a few highlights. A total of 22 safety issues were identified for which the application of CFD was considered to potentially bring real benefits in terms of better understanding and increased safety. A list of the existing databases was drawn up and synthesised, both from the nuclear area and from other parallel, non-nuclear, industrial activities. The gaps in the technology base were also identified and discussed. In order to initiate new ways of bringing experimentalists and numerical analysts together, an international workshop -- CFD4NRS (the first in a series) -- was organised, a new blind benchmark activity was set up based on turbulent mixing in T-junctions, and a Wiki-type web portal was created to offer online access to the material put together by the group giving the reader the opportunity to update and extend the contents to keep the information source topical and dynamic.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.61
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• pp.115-126
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• 2000

In General, data mining is defined as the knowledge discovery or extracting hidden necessary information from large databases. Its technique can be applied into decision making, prediction, and information analysis through analyzing of relationship and pattern among data. One of the most important works is to find association rules in data mining. Association Rule is mainly being used in basket analysis. In addition, it has been used in the analysis of web-log and user-pattern. This paper provides the application method in the field of marketing through the analysis of data using association rule as a technique of data mining.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.150-152
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• 1999

본 연구에서는 원격탐사 데이터베이스를 구축하기 위한 요구사항들을 분석하고, 원격탐사 자료의 메타 데이터 스키마를 설계하고 이를 구현한다. 특히, 현행 지형 공간 표준화 스펙을 따르는 자료구조가 연구되고, OMEGA(Object Management systEem for Geo-Spatial Applications) 객체지향 데이터베이스 관리시스템을 사용하여 SAIF(Spatial Archive and Interchange Format)를 기반으로 한 스키마 구현에 관해 기술한다. 이 연구는 차세대 데이터베이스 기술(예를 들면, 복잡한 데이터 타입 지원, 병렬처리, 사용자 편의성 인터페이스, 그리고 웹(Web) 데이터베이스 기술)에 대한 사전 기초 연구로써 실험적인 대용량 데이터베이스를 구축하기 위하여 수행되어 졌다.