• Journal of the Korean Society for information Management
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• v.20 no.1
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• pp.417-455
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• 2003

Ontologies are formal theories that are suitable for implementing the semantic web. which is a new technology that attempts to achieve effective retrieval, integration, and reuse of web resources. Ontologies provide a way of sharing and reusing knowledge among people and heterogeneous applications systems. The role of ontologies is that of making explicit specified conceptualizations. In this context, domain and generic ontologies can be shared, reused, and integrated in the analysis and design stage of information and knowledge systems. This study aims to design an ontology for international organizations. and build an Internet web retrieval system based on the proposed ontology. and finally conduct an experiment to compare the system performance of the proposed system with that of internet search engines focusing relevance and searching time. This study found that average relevance of ontology-based searching and Internet search engines are 4.53 and 2.51, and average searching time of ontology-based searching and Internet search engines are 1.96 minutes and 4.74 minutes.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.406-417
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• 2001

With the advances in multimedia databases on the World Wide Web, it becomes more important to provide users with the search capability of distributed multimedia data. While there have been many studies about the database selection and the collection fusion for text databases. The multimedia databases on the Web have autonomous and heterogeneous properties and they use mainly the content based retrieval. The collection fusion problem of multimedia databases is concerned with the merging of results retrieved by content based retrieval from heterogeneous multimedia databases on the Web. This problem is crucial for the search in distributed multimedia databases, however, it has not been studied yet. This paper provides novel algorithms for processing the collection fusion of heterogeneous multimedia databases on the Web. We propose two heuristic algorithms for estimating the number of objects to be retrieved from local databases and an algorithm using the linear regression. Extensive experiments show the effectiveness and efficiency of these algorithms. These algorithms can provide the basis for the distributed content based retrieval algorithms for multimedia databases on the Web.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.626-628
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• 2014

The Information retrieval system is more accurate of the information for you want to search, and quickly delivered. But the current search system is a simple way to parse on users fail to provide accurate information. This paper describes the ontology servers retrieve information through the system. Proposed system is Semantic Web-based information retrieval techniques in addition to structured documents using a variety of formats to maximize their data processing. In addition, interoperability and data integration RDF (Resource Description Framework) for saving documents by supporting rapid and accurate information retrieval. This supports a variety of Web browsers on the Web will be utilized in the field of efficient data retrieval.

• The Korean Journal of Archival Studies
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• no.19
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• pp.57-102
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• 2009

Recently, distribution of record via web and coefficient of utilization are increase. so, Archival information service using website becomes essential part of record center. The main point of archival information service by website is making record information retrieval easy. It has need of matching user's request and representation of record resources correctly to making archival information retrieval easy. Archivist and record manager have used various information representation tools from taxonomy to recent thesaurus, still, the accuracy of information retrieval has not solved. This study constructed record retrieval system based on Topic Map by modeling record resources which focusing on description metadata of the records to improve this problem. The target user of the system is general web users and its range is limited to the president related sources in the National Archives Portal Service. The procedure is as follows; 1) Design an ontology model for archival information service based on topic map which focusing on description metadata of the records. 2) Buildpractical record retrieval system with topic map that received information source list, which extracted from the National Archives Portal Service, by editor. 3) Check and assess features of record retrieval system based on topic map through user interface. Through the practice, relevance navigation to other record sources by semantic inference of description metadata is confirmed. And also, records could be built up as knowledge with result of scattered archival sources.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.9
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• pp.3102-3119
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• 2021

In the modern rapid growing web era, the scope of web publication is about accessing the web resources. Due to the increased size of web, the search engines face many challenges, in indexing the web pages as well as producing result to the user query. Methodologies discussed in literatures towards clustering web documents suffer in producing higher clustering accuracy. Problem is mitigated using, the proposed scheme, Semantic Conceptual Relational Similarity (SCRS) based clustering algorithm which, considers the relationship of any document in two ways, to measure the similarity. One is with the number of semantic relations of any document class covered by the input document and the second is the number of conceptual relation the input document covers towards any document class. With a given data set Ds, the method estimates the SCRS measure for each document Di towards available class of documents. As a result, a class with maximum SCRS is identified and the document is indexed on the selected class. The SCRS measure is measured according to the semantic relevancy of input document towards each document of any class. Similarly, the input query has been measured for Query Relational Semantic Score (QRSS) towards each class of documents. Based on the value of QRSS measure, the document class is identified, retrieved and ranked based on the QRSS measure to produce final population. In both the way, the semantic measures are estimated based on the concepts available in semantic ontology. The proposed method had risen efficient result in indexing as well as search efficiency also has been improved.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.21-26
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• 2006

The semantic web is an emerging paradigm in the information retrieval and Web-based system. This paper deals with a Web change detection system which employs the semantic web and ontology. While existing Web change detection systems detect the syntactic change, the proposed system focuses on the detection of the semantic change. The system detects the change only when the web has semantic change. To achieve this, the system employs the domain-specific ontology (e.g., computer science professional person information in the paper). The Web pages regarding before and after change are converted according to the ontology. Then the comparison is performed. The experimental result shows the semantic-based change detection is more useful than the syntax-based change detection.

• The Journal of the Korea Contents Association
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• v.5 no.4
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• pp.237-244
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• 2005

Currently most Internet documents including news data are made based on predefined templates, but templates are usually formed only for main data and are not helpful for information retrieval against indexes, advertisements, header data etc. Templates in such forms are not appropriate when Internet documents are used as data for information retrieval. In order to process Internet documents in various areas of information retrieval, it is necessary to detect additional information such as advertisements and page indexes. Thus this study proposes a method of detecting the layout of web pages by identifying the characteristics and structure of block tags that affect the layout of web pages and calculating distances between web pages. As a result of experiment, we can successfully extract 640 documents from 1000 samples and obtain 64% recall rate. This method is purposed to reduce the cost of web document automatic processing and improve its efficiency through applying the method to document preprocessing of information retrieval such as data extraction and document summarization.

• Journal of the Korean Institute of Oriental Medical Informatics
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• v.15 no.1
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• pp.1-10
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• 2009

In these days everyone search the information easily with the Internet as the rapid distribution and active usage of the Internet. The search engines were developed specially to accuracy of information retrieval. User search the information more quickly and variously with them. The search portal system will be embossed with representation and basic services. The Internet user needs the result of text, image and video, knowledge search. The keyword based search is used generally for getting result of the information retrieval and another method is category based search. This paper investigates the classification of knowledge search structure for oriental medicine in market leader of search portal system by ranking web site. As a result, each classification system is unified and there is a possibility of getting up a many confusion to the user who approaches with classification systematic search method. This treatise proposed the improved oriental medicine classification system of internet information retrieval in knowledge search area. if the service provider amends about the classification system, there will be able to guarantee the compatibility of data. Also the proper access path of the knowledge which seeks is secured to user.

• Journal of Information Processing Systems
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• v.5 no.3
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• pp.159-166
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• 2009

As shown in Wikipedia, tagging or cross-linking through major keywords in a document collection improves not only the readability of documents but also responsive and adaptive navigation among related documents. In recent years, the Semantic Web has increased the importance of social tagging as a key feature of the Web 2.0 and, as its crucial phenotype, Tag Cloud has emerged to the public. In this paper we provide an efficient method of automated in-text keyword tagging based on large-scale controlled term collection or keyword dictionary, where the computational complexity of O(mN) - if a pattern matching algorithm is used - can be reduced to O(mlogN) - if an Information Retrieval technique is adopted - while m is the length of target document and N is the total number of candidate terms to be tagged. The result shows that automatic in-text tagging with keywords filtered by Information Retrieval speeds up to about 6 $\sim$ 40 times compared with the fastest pattern matching algorithm.

• Journal of the Korean Society for Library and Information Science
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• v.51 no.2
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• pp.255-279
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• 2017

In a qualitative approach, this study investigated users' perceptions associated with their satisfactions in the process of using the scholarly resource search functions of the academic version of the NAVER search engine. For this study, the data was collected from a group of undergraduate students, who conducted academic information searches in the field of own major disciplinary areas, using the Web portal. Based on the data, students' satisfactions and dissatisfactions along with the reasons of their perceptions were analyzed. The results presented users' perceptions in various evaluation criteria based on the three major domains: system interfaces, retrieval mechanisms and search results. Based on the results, the study proposed the following suggestions: 1) the enhancements of the system interfaces and HELP guidances based the limited user knowledge on basic system terminologies 2) the improvements of the retrieval mechanisms associated with understanding the contexts of the search terms presented by users 3) the necessity of the user education due to the insufficient user knowledge of the retrieval mechanisms and the search functions.