• The Journal of Society for e-Business Studies
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• v.4 no.3
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• pp.179-196
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• 1999

A cyber shopping mall is a place where consumers acquire the product information and make purchase decision in the cyber space. Even though there are many advantages over traditional malls, there are still several limitations to do shopping in an existing cyber mall. One of them is the absence of efficient search tool to handle various products specifications. Existing search systems usually support the "keyword search only" with limited product information. Consumers spend lots of their time and efforts in searching products and comparing them. Recently, some web sites provide the shopping mall comparison service that supports the additional search conditions such as price and maker. These services improve the situation but it is not still acceptable. In this paper, we propose an intelligent product search system based on a mediator which supports various conditional search for each product. Our system provides consumers with search results that satisfy purchase specifications. Our system is implemented in Visual basic and pert and experimental results show satisfactory performance.

• Journal of Korean Library and Information Science Society
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• v.27
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• pp.457-483
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• 1997

This study was intended to compare the effectiveness of the Savvy search and Metacrawler in terms of the total number of relevant documents retrieved, precision, recall, and the number of deadlines. In addition, this study measured whether the Meta-search engine and general web search engines retrieved different web documents. As a result, Savvy search produced a higher precision and recall as compared with motacrawler search engine while the metacrawler had lower deadlines ration than savvy search, Also, Meta search engine was more effective than the general web search engine, The results show that the hybrid methodology of integrating a variety of web search engines can help solve retrieval effectiveness problems on the Internet.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.418-420
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• 2015

The SNOMED CT browser is a system for searching and browsing of a huge volume of medical terminologies included in SNOMED CT. Previous browsers provide a simple list-up of search results while they are similar from each other. It leads to a serious confusion in selecting an appropriate term among them. This paper presents a novel browser system which provides a comparative search of search results. To do this, the proposed system includes a terminology search module, a topology search module, and a sub-graph generation module for the results.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.19-37
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• 2016

Advance of the Internet environment is applied not only to information search but also to the area of consumption behavior. Current research analyzes online use behavior and online information search of consumers in terms of users' perception. With the result of the research, it is noticed that promotion focus brings broader variation of information use behavior, and utilitarian value has a beneficial impact on the online exploratory information search. In addition, it is revealed that the more exploratory the information search is, the wider the range of online shopping information search is. Finally, people who have utilitarian shopping value showed more exploratory behavior in online search, especially for the search of informational products, than those who have hedonic shopping value. Present research is believed to improve practical influence of consumers' personality on online use behavior when customers purchase search products online. As a result, it would contribute to consumer research and marketing held online.

• ETRI Journal
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• v.34 no.3
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• pp.369-378
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• 2012

In this paper, we propose new adaptive search range motion estimation methods where the search ranges are constrained by the probabilities of motion vector differences and a search point sampling technique is applied to the constrained search ranges. Our new methods are based on our previous work, in which the search ranges were analytically determined by the probabilities. Since the proposed adaptive search range motion estimation methods effectively restrict the search ranges instead of search point sampling patterns, they provide a very flexible and hardware-friendly approach in motion estimation. The proposed methods were evaluated and tested with JM16.2 of the H.264/AVC video coding standard. Experiment results exhibit that with negligible degradation in PSNR, the proposed methods considerably reduce the computational complexity in comparison with the conventional methods. In particular, the combined method provides performance similar to that of the hybrid unsymmetrical-cross multi-hexagon-grid search method and outstanding merits in hardware implementation.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.266-272
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• 2002

Recently various of information suppliers provide information via WWW so the necessary of search engine grows larger. However the efficiency of most search engines is low comparatively because of using simple pattern match technique between user's query and web document. And a manifest contents of query for special expert field so much worse A specialized search engine returns the specialized information depend on each user's search goal. It is trend to develop specialized search engines in many countries. For example, in America, there are a site that searches only the recently updated headline news and the federal law and the government and and so on. However, most such engines don't satisfy the user's needs. This paper proposes the specialized search engine for ocean information that uses user's query related with ocean and search engine uses the association rules in web data mining. So specialized search engine for ocean provides more information related to ocean because of raising recall about user's query

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.960-968
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• 2018

The mobile visual search service uses a query image to acquire linkage information through pre-constructed DB search. From the standpoint of this purpose, it would be more useful if you could perform a search on a web-based keyword search system instead of a pre-built DB search. In this paper, we propose a representative query extraction algorithm to be used as a keyword on a web-based search system. To do this, we use image classification labels generated by the CNN (Convolutional Neural Network) algorithm based on Deep Learning, which has a remarkable performance in image recognition. In the query extraction algorithm, dictionary meaningful words are extracted using Wikipedia, and hierarchical categories are constructed using WordNet. The performance of the proposed algorithm is evaluated by measuring the system response time.

• Journal of Engineering Education Research
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• v.19 no.4
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• pp.47-59
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• 2016

This paper explores antecedents of entrepreneurial and job search intentions based on the theory of planned behavior. Additionally, it examines the impact of entrepreneurship and job search education on these antecedents of entrepreneurial and job search intentions. The research model has been validated by analyzing 1,432 responses from undergraduate students in South Korea. The results of analysis provide several findings: First, entrepreneurship attitude, entrepreneurship subjective norm, and entrepreneurship self efficacy showed significant positive effects on entrepreneurial intention, but their effects on job search intention were insignificant. Second, while job search attitude showed significant positive effects on both intentions, job search subjective norm showed a significant effect only on job search intention, and job search self efficacy showed a significant effect only on entrepreneurial intention. Third, entrepreneurship education increased all the antecedents of entrepreneurial intention, and reduced job search attitude. These results imply that entrepreneurship and job search education should be managed comprehensively, considering their cross-effects on the antecedents of entrepreneurial and job search intentions.

• Journal of Fashion Business
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• v.22 no.4
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• pp.160-177
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• 2018

The objective of this study was to investigate mediation effect of appearance management behavior on the relationship between satisfaction of personal image and job search efficacy. Based on previous studies on components of personal image, appearance management behaviors, and job search efficacy, questionnaire items were developed. For this study, we conducted a questionnaire survey among 422 students from women's university in Seoul. Statistical analyses were performed using SPSS 23. Results are as follows. First, there were positive and moderate bivariate correlations among satisfaction of personal image, appearance management behavior, and job search efficacy. Second, satisfaction of personal image was found to have a partially significant effect on job search efficacy while satisfaction of internal image, visual image, and social image had a positive effect on job search skill. Satisfaction of internal image had a positive effect on job search strength. However, satisfaction of visual image or social image did not have a significant effect on job search strength. Third, fashion management behavior among components appearance management behavior could partially mediate the relationship between satisfaction of personal image and job search efficacy, indicating that satisfaction of internal image and visual image among components personal image not only has a direct effect on job search skill among job search efficacy, but also has an indirect effect on job search skill by affecting fashion management behavior. These results suggest that it is important to build personal image effectively and increase satisfaction with oneself through active appearance management behavior to improve job search efficacy.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.4
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• pp.745-750
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• 2009

The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.