• Journal of Digital Contents Society
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• v.15 no.5
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• pp.603-612
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• 2014

To provide efficient and correct search results, ontology which use the structure of information, is considered as a main mechanism in the semantic web. Therefore, recent research in information retrieval and data construction have emphasized the use of ontologies as a data representation and search mechanism. In this paper, we propose a semantic search method using ontology to improve search ability in web environment. Ontology and knowledge base is used to represent semantic meaning of the data and provide related web documents and facts as results. Also, search result ranking mechanism is proposed. The mechanism use cardinality of the keyword in the contents and structural information of ontology. Experimental results with several query processing indicate that different coefficient value in the expression gives different results in sample ontology system and we propose appropriate values of the coefficient.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.9-16
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• 2002

As existing analog video surveillance systems could save and retrieve data only in a limited space within short distance, it had many constraints in developing into various application systems. However, on the back of development of the Internet and computer technologies, digital video surveillance systems can be controlled from a remote location by web browser without space limits. Moreover, data compression and management technologies with Index Search algorithm make it possible to efficiently handling, storing, and retrieving a large amount of data and further motion detection algorithm enhances a recording speed and efficiency for a practical application, that is, a practical remote recordable video surveillance system using our efficient algorithms as mentioned, called WebCam. The WebCam server system can intelligently record and save video images digitized through efficient database management, monitor and control cameras in a remote place through user authentication, and search logs.

• The Journal of the Korea Contents Association
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• v.2 no.3
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• pp.59-69
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• 2002

This article purpose are on the variables of consumer's Doe sensitivity. Our result from sets of data indicate that the web site trust, the web site interactivity and the perceived risk have an effect on price search. Our result is as follows. First, the more trust the web site, the lower the price search. Second, the more interactivity of the web site, the lower the price search. Third, the greater the depth of information at the web site, the higher the price search. forth, the higher the perceived risk, the higher the price search. Fifth, the higher the knowledge of product, the higher the price search.

• Journal of Information Technology Applications and Management
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• v.16 no.1
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• pp.21-36
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• 2009

As the World Wide Web (WWW) has become a major channel for information delivery, the data accumulated in the Internet increases at an incredible speed, and it derives the advances of information search technologies. It is the search engine that solves the problem of information overloading and helps people to identify relevant information. However, as search engines become a powerful tool for finding information, the opportunities of plagiarizing have increased significantly in e-Learning. In this paper, we developed an online plagiarism detection system for detecting plagiarized documents that incorporates the functions of search engines and acts in exactly the same way of plagiarizing. The plagiarism detection system uses morpheme analysis to improve the performance and sentence-based comparison to investigate document comes from multiple sources. As a result of applying this system in e-Learning, the performance of plagiarism detection was improved.

• Journal of Information Management
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• v.38 no.1
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• pp.1-19
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• 2007

This study investigates the effect of data fusion on the retrieval effectiveness by performing an experiment combining multiple representations of Web documents. The types of document representation combined in the study include content terms, links, anchor text, and URL. The experimental results showed that the data fusion technique combining document representation methods in Web environment did not bring any significant improvement in retrieval effectiveness.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.3
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• pp.289-334
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• 2018

Even though information in many languages other than English is quickly increasing, English is still playing the role of the lingua franca and being accounted for the largest proportion on the web. Therefore, it is necessary to investigate the key features and differences between "information searching behavior using mother tongue as a search language" and "information searching behavior using English as a search language" of users who are non-mother tongue speakers of English to acquire more diverse and abundant information. This study conducted the experiment on the web searching which is applied in concurrent think-aloud method to examine the information searching behavior and the cognitive process in Korean search and English search through the twenty-four undergraduate students at a private university in South Korea. Based on the qualitative data, this study applied the frequency analysis to web search pattern under search language. As a result, it is active, aggressive and independent information searching behavior in Korean search, while information searching behavior in English search is passive, submissive and dependent. In Korean search, the main features are the query formulation by extract and combine the terms from various sources such as users, tasks and system, the search range adjustment in diverse level, the smooth filtering of the item selection in search engine results pages, the exploration and comparison of many items and the browsing of the overall contents of web pages. Whereas, in English search, the main features are the query formulation by the terms principally extracted from task, the search range adjustment in limitative level, the item selection by rely on the relevance between the items such as categories or links, the repetitive exploring on same item, the browsing of partial contents of web pages and the frequent use of language support tools like dictionaries or translators.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.684-686
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• 2014

It is difficult to effectively search and data management due to the increasing number of web is now. While Semantic Web technologies and the development of next-generation wepin this as a way to overcome them, and monopolize the domestic utilization is not overwhelming introduction to the Semantic Web technology is being used in existing search engines. This causes the development of the Semantic Web is becoming slower, and reluctant to use the Semantic Web users who use search engines as well. In this paper, compared to the currently used web and the next generation of the web, and why utilization is low compared to the search engine you are using an existing Web technology that uses the Semantic Web technology is a search engine, what research was that the inefficient because, as a RDF-based Semantic suggest how to improve the efficiency solved by designing the web.

• Archives of design research
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• v.15 no.1
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• pp.93-100
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• 2002

The University's web library is a form of library that enables to deal with information about searching loaning, returning of books or data housed in it through web. With the advent of the network and multimedia following the entrance to an information-oriented society, we are experiencing a big change in how to communicate and acquire information. Massive multimedia information transmitted by image and moving picture through the network, made it possible to overstep the limit of the physical gap between information suppliers and users. Despite this important role, it is accompanied by problems such as copyright, scarcity of recognition, paralysis of infra, technical matters and reliability which demand development. In this thesis, according to the State University Evaluation Standards, search node and user interface by system used in 20 different universities possessing web-based library sites were compared are analysed. On the basis of this, an experimental user interface for web-based University libraries was produced, and various questionnaires and data leer this produced interface were collected, classified and analyzed. With the application of the results for the work above to the general search system interface of the web-based library, we proposed a new user interface that contains the following functions, such as location and loan condition of books, search frequency and steps for purchasing books inside the web library.

• Proceedings of the Korean Statistical Society Conference
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• 2005.05a
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• pp.263-269
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• 2005

Users who use Web site wish to get information conveniently. To users who web site operators use Web site differentiation to provide done service pattern analysis by user do must. Association rule is one of data Mining techniques for pattern discovery. If search for pattern by user, differentiation by user done service offer can. Association rule search result that pattern by user can know, and considers web page visiting time for association rule search differentiation done web structure service and recommendation service possible.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.147-157
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• 2018

Since Google launched a prediction service for influenza-like illness(ILI), studies on ILI prediction based on web search data have proliferated worldwide. In this regard, this study aims to build short-term predictive models for ILI in Korea using ILI and web search data and measure the performance of the said models. In these proposed ILI predictive models specific to Korea, ILI surveillance data of Korea CDC and Korean web search data of Google and Naver were used along with the ARIMA model. Model 1 used only ILI data. Models 2 and 3 added Google and Naver search data to the data of Model 1, respectively. Model 4 included a common query used in Models 2 and 3 in addition to the data used in Model 1. In the training period, the goodness of fit of all predictive models was higher than 95% ($R^2$). In predictive periods 1 and 2, Model 1 yielded the best predictions (99.98% and 96.94%, respectively). Models 3(a), 4(b), and 4(c) achieved stable predictability higher than 90% in all predictive periods, but their performances were not better than that of Model 1. The proposed models that yielded accurate and stable predictions can be applied to early warning systems for the influenza pandemic in Korea, with supplementary studies on improving their performance.